Building functional teams for the IoT economy

Experts weigh in on more fluid approaches to IoT team building.

Download a free copy of our new report, “When Worlds Collide: Hardware, Software, and Manufacturing Teams for the IoT,” by Mike Barlow. Editor’s note: this post is an excerpt from the report.

You don’t have to be a hardcore dystopian to imagine the problems that can unfold when worlds of software collide with worlds of hardware.

When you consider the emerging economics of the Internet of Things (IoT), the challenges grow exponentially, and the complexities are daunting.

For many people, the IoT suggests a marriage of software and hardware. But the economics of the IoT involves more than a simple binary coupling. In addition to software development and hardware design, a viable end-to-end IoT process would include prototyping, sourcing raw materials, manufacturing, operations, marketing, sales, distribution, customer support, finance, legal, and HR.

It’s reasonable to assume that an IoT process would be part of a larger commercial business strategy that also involves multiple sales and distribution channels (e.g., wholesale, retail, value-added reseller, direct); warehousing; operations; and interactions with a host of regulatory agencies at various levels of government, depending on the city, state, region, and country.

A diagram of a truly functional IoT would look less like a traditional linear supply chain and more like an ecosystem or a network. The most basic supply chain looks something like this:

Supplier → Producer → Consumer

If we took a similarly linear approach and mapped it to a hypothetical IoT scenario, it might look something like this:

Entrepreneurs → Capital Markets and Investors → Sales → Software Development → Hardware Design → Prototyping → Manufacture → Warehousing → Distribution/Logistics → Wholesale → Retail → Consumer Markets → Customer Service → Finance → Legal → HR → Regulators

Even an abbreviated description of a hypothetical IoT “supply chain” reveals the futility of attempting to map a simple linear sequential model onto a multi-dimensional framework of interconnected high-velocity processes requiring near-real-time feedback. A practical IoT ecosystem model would look something like this:


Sketch of a hypothetical IoT ecosystem.

In all likelihood, the IoT economy will resemble a network of interrelated functions, responsibilities, and stakeholders. The sketch only gives a rough idea of the complexities involved — each node would have its own galaxy of interconnected processes, technologies, organizations, and stakeholders. In any case, it’s a far cry from simple “upstream/downstream” charts that make supply chains seem like smoothly flowing rivers of pure commercial activity.

Unlike traditional software development scenarios, IoT projects are undertaken with the “real world” clearly in mind. It’s understood that IoT services and products will “touch” the physical universe we actually live in. If the assignment is developing new parts for jet engines used by passenger airlines, there will be real consequences if the parts don’t work as promised.

A more fluid approach to team building

Working relationships between software developers, hardware designers, and manufacturers within IoT ecosystems are still taking shape and evolving. The structure, staffing, and organization of a team would depend largely on the project at hand and the depth of available talent.

“There isn’t an ideal team. You have to start with the problem and work backward to discover what is available and commoditized, and what really needs to be created to make a solution real,” says Andrew Clay Shafer, senior director of technology at Pivotal, a company that provides a cloud platform for IoT developers. “The dream team would have unlimited resources, expertise, and imagination. Realistically, you won’t have a dream team, so you are better off examining the problem, looking at your available resources, and filling in gaps.”

Mike Estee, CTO and co-founder of Other Machine Co., a company that builds machines and creates software for desktop manufacturing, says the firm looks for software developers with experience in “building consumer-facing applications that integrate directly with hardware designed in tandem” and hardware designers who can bring products to market “on time, on budget, and with a high degree of polish.”

Ayah Bdeir is the founder and CEO of littleBits, a company that creates “libraries” of electronic modules that snap together with magnets. An advocate of the open source hardware movement, she is a co-founder of the Open Hardware Summit, a TED Senior Fellow, and an alumna of the MIT Media Lab. From her perspective, the “ideal” development team includes hardware, firmware, software, and Web experts. Tightly integrating the design function is absolutely critical, she says.

“Design is crucial at the very beginning. Our second hire in the company was an industrial designer, and it has transformed our business and our product,” Bdeir says. “Specific skills and languages don’t always mean as much as the ability to adapt. The team needs to be creative, agile, and quick to learn.”

While software development is considered a relatively “mature” field, the need to combine software development and hardware design has spawned a host of new problems. In an email, Bdeir shared her view of the current situation:

For software developers, a lot of the barriers have been removed. Today, you can prototype and launch a software product with very little time, money, and most importantly, few external dependencies. When you see there is traction, you can scale your offering gradually, and not overextend yourself financially.

For hardware, the barriers are much more defined and difficult to deal with. You can prototype a lot faster, and get initial interest/traction through Kickstarter, press, or showing off your product at events. But there is a pretty big step to getting first-run manufacturing done.

Finding manufacturing partners who will help you make your product manufacturable is hard when you are at a small scale, and it takes a lot of time. When we were starting out, we had to manufacture our magnetic connector with a factory that made plastic insoles and knee guards because I couldn’t find any manufacturer that knew electronics or connectors that would take me seriously.

Estee, who spent nine years as a software engineer at Apple, has a similarly chastened view of the challenges. Here’s a brief excerpt from an essay he posted recently on Medium:

If you’ve never started a hardware company before, it’s very hard to understand the vast differences between a prototype, a product, and a company that supports it. A product is so much more than just the machine. It’s also the packaging, the quality assurance plan, the documentation, the factory, the supply chain, vendor relations, testing, certification, distribution, sales, accounting, human resources, and a health plan. It goes on and on. All things you probably weren’t thinking about in the rush to get the Kickstarter launched.

Indeed, the complexities seem nearly inexhaustible. Shafer describes the challenges from an industry-wide perspective:

As we move into a world where all things are integrated, the stack is getting wider and deeper. The choice is between building teams that have expertise at each level … or choosing platforms to do the heavy lifting and act as force multipliers for teams with more focused skills. The challenge is deciding which problems to solve yourself and which to outsource.

People get excited about creating ‘things,’ but the Internet is the other half of the equation, and there are still hard problems to solve there. Even moderate IoT build-outs could quickly create sensor networks that have latency, scaling, and analytics problems that only a handful of the big Web companies have had to solve until now.

Today, there is no equivalent to the LAMP1 stack for the IoT. It will be several years before a common way of solving IoT problems begins to emerge.

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