Tech Data Bridges the IoT Partner Ecosystem Gap

How Tech Data EMEA Bridges the IoT Partner Ecosystem Gap

April 19, 2022

Kenton Williston

IoT partner multiverse

Digital is the name of the game these days—for pretty much every game in town, every business, every service. But digital transformation takes expertise and skills, and small- to medium-size companies can’t usually afford a big R&D department. They may not have the right resources in-house to deal with complex and interconnected technologies like computer vision, either. Fortunately, there is an ecosystem of IoT partners that can help.

But who services the service provider? Who sells to the channel reseller? Who integrates the systems integrator? That’s where Tech Data EMEA, a leading IT distributor and solutions aggregator, comes in. Its European Chief Technologist for Data and IoT Evan Unrue talks about overcoming barriers to entry for technology deployment, the solutions Tech Data supports, and its crucial Better Together alliance with Microsoft and Intel^®.

What drives enterprises toward AI and IoT today?

Everything is digital these days. It’s forcing enterprise organizations to become more real time, more data driven, more informed, and more engaging across both their southbound channels down to the customer, and upstream with how they interact with their suppliers.

Data is also now absolutely critical to strategy. And rather than data just being something that’s generated as a byproduct of an application, data is driving applications. Look at supply chain, for example. Organizations are now having to deal with the fact that customers want to know where everything is, where it came from, is it ethically sourced, is it going to come tomorrow? All this requires an enormous amount of orchestration, which requires data and intelligence.

How have companies been doing in their efforts to deploy these kinds of technologies?

We’ve seen adoption really springboard over the last couple of years. Five years ago you had to be a Fortune 500, a Fortune 1000 company with an R & D budget to afford to do these projects and then drive them into the core of a business. And the SME market was suffering because it wasn’t able to do that. Or they were creating interesting projects, but they weren’t really driving them towards the business outcomes.

“All of the complex things that you can do with #AI or with #IoT at scale should be reserved for where the right budget exists, and where the payoff is big enough.” – @interestingevan, @TechDataEurope via @insightdottech

In the last couple of years, we’ve seen more success in companies being laser focused on outcome. A big part of that is due to the efforts of the vendor community—that’s the likes of Microsoft, the likes of Intel^®—driving an immense amount of innovation through their ecosystems. And the ISVs and OEMs are solutionizing off the back of all that. So we’re seeing solutions come into the market that are more clear and concise in terms of the outcomes that you can drive with them.

What is Tech Data and its IoT partners doing to ease the barriers to AI and IoT?

For common industry challenges there should be off-the-shelf offerings that can be implemented by the average business stakeholder. We’ve seen a bit of a democratization around certainly AI, and around some of the application stack that sits in front of these IoT infrastructures. We have a big push towards solutions at Tech Data, and you only have to go on the websites of Microsoft or Intel^® for two minutes to see their efforts around driving market-ready solutions, off-the-shelf solutions.

All of the complex things that you can do with AI or with IoT at scale should be reserved for where the right budget exists, and where the payoff is big enough. But if you are a small freight-logistics company, you’ll typically have the same problems of any other small freight-logistics company—whether it’s optimizing your fleet and their routes and their maintenance, or whether it’s tracking assets through the supply chain. Whatever it is, the solutions should be off the shelf and ready to take to market.

I think some of these complex technologies fall into the category of digital transformation as a whole, and attacking that can be a scary thing for a midmarket organization. So you have two approaches. You can either come with a top-down approach and have a uniform infrastructure that all these use cases can plug into; it’s a bit of a larger effort, but the payoff is there. Or you can look at the discrete parts of your business operations where you might have gaps in data, and then start to deploy these tactical solutions.

There’s a spectrum of solutions out there; the Intel^® IoT Market Ready Solution program is one. But primarily it’s about taking proven solutions by ISVs, OEMs—companies that have deployed these solutions over and over with customers—and our job then is to provide the reach and scale of getting those solutions in front of a channel partner.

Can you talk about some specific use cases and technologies Tech Data supports?

Smart building is certainly a big area, and there are a few facets to that. Number one is how do you better manage and maintain a building? How do you reduce the cost of doing that? How do you get in front of problems as they’re happening? And within that area, energy is a big topic. Certainly a lot of companies are being tasked with being more proactive with their sustainability efforts.

Another one we’ve seen over the last few years is retail in the High Street looking to reassert its resiliency—giving people more reasons to come, being engaged with customers, and extending those customers’ digital journeys into the physical store. Better planning of store layouts, for example. Better optimization of marketing to the demographics on the ground leading to better conversions. A colleague of mine likes to use the term “phygital,” which is the combination of physical and digital, and this applies particularly well in the High Street. It’s being contextual in terms of how you interact with a customer, and that might be through signage, that might be through interactive displays and putting something in front of a customer that’s relevant.

How does your work with Microsoft and Intel^® relate back to these solutions?

Those two organizations have coexisted in the enterprise space for a long time. And with regard to technologies like IoT, for example, there’s been a really strong focus from both of them to be promoting the industry applications around it.

If you look at Intel, it’s really been driving programs to simplify the development process, and help developers and organizations build these solutions at the edge—bringing on technology such as computer vision, using tool kits such as OpenVINO^™, to create meaningful solutions. And you pair that with all the expertise and experience that Microsoft brings—and not just from the cloud. It ranges all the way from being able to do really complex and difficult, but very powerful and insightful things in very bespoke environments, through to very plug-and-play-type offerings that are really geared towards the midmarket. It’s kind of “one plus one equals five.” It’s a very powerful combination.

How is Tech Data bringing value to this alliance as an IoT solutions aggregator?

One of the big challenges historically, from a technology standpoint, has been understanding and identifying the multiple stakeholders required to bring these solutions together. So part of our job is to aggregate all the different technology players within that value chain, and to simplify the consumption of those solutions so resellers and customers don’t have to get bogged down by the technology.

As far as Intel goes, it’s a little bit removed from the coalface in terms of who’s selling what, and we connect them to that through our interactions with the resellers. And with Microsoft we’ve had a keen joint focus around IoT since the beginning. So I think there’s just strong alignment, a strong execution capability, and we complement each other in all the right ways.

What are some of the trends that businesses should be thinking about going forward?

One of the big things we’re seeing now is leveraging AI to make sure that insight into the data is driving what the action should be. This is what we see from a lot of the ISVs we work with. They’re focusing on what the action should be, what the outcome should be, rather than just gaining visibility and transparency into whatever is being monitored.

Computer vision looks like a really strong trend to me, just because it’s such a versatile technology. It can underpin countless use cases that could range all the way from traffic control and waste management and public safety from a smart city perspective; to gaining richer insights and stronger engagement from a retail perspective; all the way through to improving things like quality and safety in warehouse environments.

Are there any big IoT challenges that companies should be aware of?

I think the biggest thing is getting the support of the wider business. One of the challenges of IoT is that the first use case provided might not actually be the one that delivers the whole ROI. So it’s really important to try to understand who the different stakeholders are that are going to benefit from these solutions, and to bring them to the table. In retail offerings, for example, there are some things that just have to be done, regardless of ROI. Certainly retailers don’t want to have to close stores because they can’t meet conditions around, let’s say, proper social distancing.

But when it comes to looking at digital engagement within the store, when you start to bring it to the planning side of the business, and to the marketing side of the business, and you start to bring in, maybe, merchandising and third parties that advertise, and offer them space and data around footfall—then it helps the payoff become a lot more substantial in terms of justifying the business case.

I like to call it the IoT multiverse, because there are so many different dimensions in terms of the type of companies that play here—whether it’s the connectivity channels, the silicon channels, or the cloud channels.

Anything else you’d like to leave us with?

The importance of edge compute. We’ve seen technology architectures go from distributed to centralized, to distributed, to centralized, and back and forth. But this is one of the things that’s really become critical—certainly with the adoption of IoT, where you have mass amounts of data being generated at the edge, and that data might actually need to be processed, or might impact a process at the edge. Edge computing is becoming pretty critical because of the volume of data that can be created, and with an organization’s ability or need to drive action rather than just deliver data off the back of these solutions.

Whereas the cloud, whilst powerful and important for all of the things that I’ve mentioned in terms of getting a broad view across multiple assets, across multiple locations, having more horsepower behind you to drive deeper and richer insights—all of that’s important, but being able to automate and drive AI locally is also important. Microsoft acknowledges that actually some of the services it provides it needs to be able to push to the edge as well as having in the cloud, which is something that it does hand in hand with Intel.

Also, one of the things I’ve always said is that, as distributors, we have one of the most privileged positions in terms of being able to derive insight from the market. We get to see the hopes and dreams and fears of all of our vendors—what they’re trying to achieve and what their strategies are. And then, at the other end of the spectrum, we get to see what the partners are doing. Where their strategies have evolved or haven’t. Who are the early adopters, and who are the laggards? How do we help them move from one bucket into another and maintain relevance in the market?

And because we’re really sitting in between all of that, we are perfectly primed to bridge the gap between the vendors’ aspirations and their knowledge, their technologies and expertise, but also our understanding of those channels and how to drive adoption into the right technology spaces.