Selecting an IIoT platform vendor can be a long and daunting process. Not only does it involve sitting on many demo calls, but it also requires the coordination of many team members for various checkpoint approvals.
Having worked with manufacturing companies for the last decade, we’ve seen companies ask all kinds of questions during their vendor selection process. Here are our top dos and don’ts for making the most of your IIoT platform demo experience to save you both time and energy—and make sure you end up with the right solution from the start.
Tip: Before you start demos, evaluate if you have the team and strategy in place to make the decision. If so, focus your demos on hitting that strategy. If you’re still in the inquiry phase of defining your Industry 4.0 roadmaps, check out complimentary resources here.
Do come prepared with persona data profiles
One of the best ways to prepare for an IIoT platform demo is to think about the people at your organization who will benefit the most from utilizing more data. Consider why you want certain users to have access to data. What should they be able to do with data that they can’t do today?
For example, consider the role that data currently plays in the lives of your operators. Maybe they have access to retroactive data—such as what happened in production last week or month—but they don’t have access to live data.
How would access to live production data change the way they work? What kinds of problems could they solve with live data that they can’t solve with week-old reporting data? How much time would they save with the addition of remote monitoring tools, easy-to-access dashboards, and automated reports for morning meetings?
If you’re struggling to think of each individual’s benefits, start with the bigger picture. Why does your organization want to use data in a better way? Is the goal to capture more market share? Is there an initiative to implement new technologies? Do you have sustainability targets with aggressive goals?
IIoT platforms often have a ripple effect, spanning benefits across the entire organization. Starting with this overarching question can help you narrow down data use cases for the different data users in your organization.
Don’t focus on specific connectors
In today’s highly connected metaverse, connectors are almost a dime a dozen. The reality is that nearly all of today’s IIoT platforms can connect to your existing systems. Comparing vendors based on specific connectivity needs can take up valuable demo time, hindering what you can learn about the platform’s unique capabilities.
Remember that you shouldn’t try to build your entire IIoT strategy around a single existing system your company is currently using. The goal of an IIoT platform is to embrace holistic data usage from IT to OT, and from frontline workers to top management. Yes, this means ensuring compatibility with your existing systems, but with the rise of containerization and open-source software, your company should consider the short-term growing pains with time to value and the longevity of a solution.
Look beyond the way things are currently being done and consider an IIoT platform as your data foundation that brings to your organization a new, comprehensive way of working with data. Finding a vendor that will address your concerns and build with you can further reduce the risk of being too focused on a specific tech feature.
Do think beyond a single use case
When researching different IIoT platform vendors, it can be tempting to lock into a single feature offered by the solution. For example, you want to reduce energy consumption on one asset. However, isolating your focus to a single use case is like the old adage about using a hammer as your only tool when you have an entire toolbox. In the end, everything will start to look like a nail, even if it’s not.
Ultimately, the challenges your company faces aren’t one-sided. There are diverse data needs at all levels of your organization, ranging from predictive maintenance strategies to benchmarking performance to defect recognition via computer vision. You need a variety of tools to address a wide array of challenges—both now and in the future.
Let’s say your company is looking at an IIoT platform specifically as a data repository. (Curious about data lakes? Read about different kinds of data management solutions for manufacturers.) If you’re limiting the platform’s value to something as rudimentary as a data repository, you could be missing out on asking bigger questions about the platform’s data transformation capabilities, AI features, or reporting tools.
For example, Braincube has a suite of applications that address a variety of pain points specific to manufacturing. Our app packages are built around key industry challenges, ranging from process and quality control to predictive maintenance. However, the apps aren’t limited in terms of their functionality. Each application can be used in multi-faceted ways to fit specific KPIs depending on your company’s top challenges.
Thinking about these challenges ahead of time can help you ask the right questions about a platform’s full capabilities, not just the most pressing problem of the week.
Do think about solving problems in new ways
Speaking of problem-solving, one misstep we see a lot of prospective customers make is trying to fit a new tool into their existing way of working. It is true that an IIoT platform will expand the capabilities of what your teams can do. However, the right tool should also change the way teams look at problems.
Consider working in a paper manufacturing facility. Right now, the team wants to better predict when a paper break is coming. But what good is knowing that a break is coming if it doesn’t really change what the team is capable of fixing? Predicting the break may enable teams to have the right replacement parts on hand, but it will likely still result in unplanned downtime, production loss, and frustration.
A better solution would be to eliminate paper breaks altogether. If teams could identify why breaks happen, they can work towards eliminating paper breaks entirely. If this happens, you’ll likely see many secondary success indicators. For example, a production line consistently running with no paper breaks could see improved uptime, better scheduled (and predicted) maintenance, and higher quality scores.
Tools like Braincube can help with these overarching problem-solving approaches. Using the above example, our tools could help teams understand the optimal operating conditions for minimizing paper breaks. By operating within these optimal recommended conditions, teams will likely solve other problems simultaneously instead of only focusing on predicting paper breaks.
Don’t just look at hard ROI
It’s a problem we see often during the vendor selection process: corporate teams want specific cost savings and hard ROI proof before investing in a new technology or solution. Finances are certainly important when it comes to selecting an IIoT platform, but it shouldn’t be the leading pillar of your selection process.
One of the key issues with this approach is that it’s often very difficult to assess the financial value of implementing an IIoT platform at your organization. Is it possible to put a price tag on solving problems faster? What about the shift in the way teams collaborate with other departments to address a wider range of issues?
Your company is almost guaranteed to see cost savings after implementing IIoT solutions, but it can be difficult to pinpoint these savings to a single source. Instead, focus on the “soft savings” you’ll gain from using IIoT tools: time savings, streamlined processes, and more comprehensive utilization of data.
Do consider “hidden” fees from IIoT platform vendors
When it comes to software-as-a-service vendors, consider what is and what is not included in your offer. Knowing the granularity of what is included in your service agreement will save you from unpleasant bills in the future.
For example, are there integrator fees, build fees, license fees, or something else? How do people access your tool? Do you pay by an annual fee, per user, or per line?
Sure, your organization will evolve over time and you will likely need to make choices like whether to build or buy applications. Still, understanding how pricing is broken down is critical to making the case for an IIoT solution.
There’s no shortage of solutions available in today’s market and they all offer seemingly similar solutions that vary ever so slightly. Identifying your must-haves and nice-to-haves (prior to your demo) can help you stay focused on what you need. This is far preferable to the vendor telling you what you need.
Digital transformation is such a large endeavor that it must be met with a collective approach. Piecemeal, one-off projects are not going to revolutionize your organization. If you’re going to make big strides, you need to move everyone together at once (even if it means incremental progress at first).
In our experience working with thousands of manufacturers, we’ve discovered that the companies with successful digital transformations start by aligning goals, strategies, and initiatives at the top of the org chart. Executives should work together to generate clear goals and objectives that resonate across the entire organization.
Do consider your long-term data journey
Lastly, it’s important to remember that IIoT solutions are not designed to solve today’s problems. No matter where you are currently in your data journey, the reality is that you will need Industry 4.0 tools at some point in your company’s future. Many Industry 5.0 topics are starting to gain traction, but you can’t get to 5.0 unless you hit the 4.0 stepping stone first.
Even with the right technology, you also need to ensure the people at your organization are included as you enhance your data culture. People are at the heart of digital transformation. Assuring that they are part of the journey—instead of along for the ride—can make a big difference in technology adoption once you select your vendor.
It’s important to look at your goals in the next six months, but digital transformation is an ongoing journey. Industry 4.0 tools, like an IIoT platform, will continue playing a critical role in your company 10 years down the road. Asking the right questions today and thinking about the bigger picture will be immensely helpful during your IIoT platform vendor selection process. This can ensure you’re finding the right partner (and tool) to grow with your business.
Summary
It’s tempting to attend an IIoT platform demo with a laundry list of technical questions or to better understand market offers. However, ensuring that you know what you hope to achieve by embracing technology can help to focus your efforts. Many companies are so tuned into the biggest challenges of the moment that they lose sight of a wider range of opportunities.
Preparing for an IIoT platform demo with a more integrated strategy in mind can help you uncover key missing links or surprise value-adds. This can save you both time and money in the long run by ensuring you find the right partner from the start.
Manufacturers need to easily access data from their production processes to take advantage of the new inroads available with Industry 4.0. Driven by the need to identify, analyze, and optimize industrial data, many manufacturers are considering (or have already adopted!) an Industrial Internet of Things (IIoT) platform to leverage the power of Machine Learning, AI, and Big Data discoveries.
While there are plenty of examples of best practices for implementing an IIoT platform, these five less-obvious approaches may be the key to helping drive a successful implementation. From choosing the right platform to multi-facility rollouts, these considerations can help you transition from a successful implementation to a successful Industry 4.0.
As organizations move more of their data to the cloud, you’ll need an IIoT platform that protects you against cyber security threats. From the way your platform processes your data to how your employees access that data, cybersecurity cannot afford to be an afterthought in your journey to Industry 4.0. Learn some of the best practices in protecting your organizational data against imminent cybersecurity threats.
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Introducing predictive analyticsDive deep into your processes to uncover hidden improvement opportunities. Detect patterns, prevent downtime, and reduce costs.
Introducing predictive analytics
Dive deep into your processes to uncover hidden improvement opportunities. Detect patterns, prevent downtime, and reduce costs.