But can we transport the camel to the right buyer? Do you have the right pallet for it? The right go-to-market (GTM) strategy is needed to ensure you have product-pallet fit to reach your buyers in a connected world.

How your GTM adapts for a connected world is as important as reimagining your product strategy through a business model and consumption-centric lens, not a technology-centric lens.

To see adapting our GTM, we need to look at how these IoT offerings are sold and bought.

IoT requires the convergence of IT and OT. Simply put, IoT = IT + OT

Hence, we will start by looking at channel partner structure in IT and OT worlds and then show them side-by-side to see the almost bewildering impact on GTM strategy when IT meets OT.

GTM Partner Types

Regardless of whether your company plays in IT or OT, it’s important to take a look at the players in any GTM partner ecosystem before we complicate the discussion with IT+OT combo issues in GTM.

While Cloud continues to challenge traditional models for GTM, knowing the basic taxonomy and partner types is essential before you adapt them for IoT-Cloud. So, let’s look at that first. (If you are a purist, note that I’ll be using the words channel and partner interchangeably in this article to refer to GTM partners.)

For any product maker, whether IT or OT, the GTM ecosystem looks like this:

Key points to note from this value chain view:

• Maker to Buyer: Left to right is the commercial and operational pathway for products to get to the right customers.
• Direct, Indirect, Tier-1, Tier-2: GTM channel is split into direct vs. indirect and tier-1 vs. tier-2; Indirect splits into tier 1 or tier 2 if an intermediary like a distributor is involved.
• Other Makers: Makers may sell to other makers. This is an OEM/ISV channel (also referred to as technology partner). Know that each OEM/ISV has its own GTM ecosystem facing buyers and it mimics the original maker’s GTM channel structure.
• ISVs: As your offer becomes cloud-delivered and accessible programmatically (via APIs), you will need to foster a software vendor ecosystem that needs to either run on your products or use your products to integrate with other solutions.
• Service Partners: The players in green are service partners who provide consulting (business and technology), resale, integration, and operational support and management (e.g. Managed Service Providers, MSPs). A given player might have multiple services practices that comprise their overall business (e.g. integration and managed service).

You will see different firms use different ways to describe and categorize these partner types. For example, Amazon Web Services simply clubs all the service partners under “consulting partners” umbrella. Some others might call them solution providers, and so on.

Be aware of the partner role and value-add when you develop your GTM strategy. Normalize the taxonomy for your business’s needs.

GTM for IT + OT

Having mapped out the generic ecosystem layout, let us now simply put the ecosystems for IT and OT makers side-by-side, for example, by pitting KUKA, the robot maker and Dell, the IT maker together.

For simplicity, I have collapsed the different GTM players inside the grey boxes rather than show every role from the prior graphic.

The picture suggests that IT Maker sells to IT buyer and OT Maker sells to OT buyer and the twain meets when IT and OT collides inside an organization to make the IT+OT solution work!

Intuitive? Perhaps. Sounds like a terrible idea? Of course, it is.

Such an approach will never get adopted or scaled for many reason:

1. It’s inefficient with so many B2B hand-off’s in the value-chain.
2. The onus to get the solution right falls on customer’s OT ops and IT ops.
3. Will you find enough KUKA-Dell talented people to make it all work?

Here lies the entire reason to rethink GTM strategy. You have to foster solution-thinking further upstream in the value chain. Not at the staging site of the customer. AND you have to foster collaboration across the value chain.

Selling scalable IoT solutions require collaboration across the value chain as well as up-front integration of the solution, long before it reaches the buyer.

The resulting picture looks like this:

It shows industry-level collaboration to create the right IoT solutions and take it to market.

Let’s be realistic too. It isn’t going to be all harmony all the way. While collaboration is essential, it will be forced on players in the value chain who are currently competitors, causing the dynamic that I call Frenemies and Knotted Value Chains. But eventually customer success will drive the right behavior.

Summary

I have barely scratched the surface of GTM strategy in the IoT world. We saw the complexity involved.

As the product itself is changing to become consumption-centric, the offer evolution is pulling traditional channel deliverables like support, management, and integration to the cloud, towards the maker, as part of the consumption-friendly delivery of the product.

There is a horizontal pull of deliverables towards the Maker and a concurrent need for vertical integration of expertise between OT and IT partners.

We can see why most organizations struggle to navigate this transition to consumption-friendly IoT and orchestrating the IT+OT ecosystem. It requires changes on multiple fronts at the same time:

1. Consumption-centric offer
2. Subscription financial models
3. Channel orchestration
4. And direct and indirect channel incentives, just to name the top challenges.

Who said life is easy when IT meets OT? It’s simply is exciting.

—–

First published at IoT For All, a leading technology media property dedicated to providing the highest-quality, unbiased content, resources, and news centered on the Internet of Things and related disciplines.

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If connectivity to improve existing business operations is the sole purpose of IIoT, aren’t we squarely suffocating inside the dilemma-filled innovator’s box? Can we reimagine the killer app or the killer product? Luckily, we can. All we need to do is take a consumption-centric view of product strategy.

IoT enables us to take a consumption-centric view to creating new offerings

Consumption-centric Product Strategy

Historically we built products with a technology-centric view. For example, in the IoT world it amounted to thinking about how to integrate sensors and computers in our largely electromechanical products; how to connect them with the plethora of communication mechanisms available to us (3G, LoRa…); how data was exchanged etc. All that is needed. But that is still thinking of the offer from a technology-centric lens, not a consumption-centric lens. Kindle did it.

IoT Killer App and Kindle

Kindle didn’t subject us to worrying about connectivity, subscription to a wireless plan, or maintenance. Buy a digital book, read it, or buy a subscription and keep reading. Simple enough, but how shall we do it in our industrial world?

There are two ways to reimagine your connected products in a consumption-centric manner: 1) Change the consumption model of your existing product OR 2) Offer a new product or service via your connected product

The former is like offering a robot-as-a-service instead of selling a robot outright. The latter is like selling site-security for a warehouse and using robots to deliver it, or like delivering a book over a Kindle. Kindle isn’t the IoT product. It is a mere delivery mechanism.

Reimagining Offers: Dimensions of Consumption

To reimagine your offerings for a connected world, think about these dimensions of consumption for your offer, any offer. The following graphic illustrates this:

The dimensions convey the following:

• Mode: How the end consumer or user gets your product: it comes in a package, comes as a service on-demand, comes digitally, delivered as audio etc.
• Ownership: Whether they chose to own your product or buy rights to use when needed. e.g. lease vs. buy
• Operations: Whether they operated it themselves (“self-driven”) or had someone else operate it for them (“chauffer-driven” or vendor-managed vs. self-managed)
• Payment: Did they pay to use each time or subscribe to it?

The simple variations under M-O-O-P dimensions are shown below:

Let’s mix and match the above and see how existing offerings in the market use these dimensions:

• Leased Car: Mode 1 (Packaged), Ownership 2 (leased for term), Operations 1 (you are driving it), Payment 2 (periodic payments over term). i.e. M1-O2-O1-P2 consumption pattern.
• Lyft (since it is politically incorrect to use Uber as example these days): M2-O2-O2-P1 consumption pattern.
• Connected Robot for Zero Down Time: M1-O1-O1-P1 pattern. Assumed capex spend and managed by the enterprise owner. As ho-hum as you can get. No killer app here! (I suppose the robot can’t be a killer app, lest it violates the laws of robotics.)
• Cloud computing: M2-O2-O2-P1 pattern. Assuming it’s pay-as-you-use pricing for Infrastructure-as-a-service (IaaS).

…and so on and so forth for any product you analyze. This pattern of transformation is an easy key to re-vector your business model.

Killer Business Models, Not Killer Apps

Last week I came across a robotics startup that offers a site-security solution based on robots (like a monthly subscription to ADT or Brinks for home security in the US). So it’s not killer apps that are coming, but killer business models and killer solutions.

Let’s at least march towards making our products more consumption-centric, if not start delivering new services on top of our existing products. Time to get beyond the predictive-analytics-for-maintenance cliché and reimagine our offerings before someone else beats us to it.

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Visit TheCerebrus.com for more discussion on IoT and Digitization where we provide nuggets from our think tank. © The Cerebrus Group. All Rights Reserved.

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Discussions about edge computing in the recent years reminds me of how far we have come in distributing computing and how many types of “edge” computing there are. There are many edges to consider, which I think of colloquially as: the Cloudy Edge, the Business Edge, and the Personal Edge. A more apt term for all this perhaps is proximity computing.

The Economics of Proximity Computing

First, a quick look at the economics of proximity computing, as we think of the different edges. Events in our world need a timely response either for good user experience (“changing TV channels”) or to avoid catastrophes (“gas line leak”).

We need to choreograph complex systems to Sense, Process, and Act (SPA)as events occur. The cost of SPA’ing is a function of local vs. remote processing costs, network connectivity costs and remote systems management costs.

Size and power aside, proximity computing balances the timeliness of responding to an event with the cost of that response.

The three edges — cloud, business, and personal edges — deploy SPA to a varying set of problems in different environments, for the purpose of optimal, automated response.

The Cloudy Edge

This is the least talked about Edge. Even before our team tried to put computing on a branch router, there was a network edge — a topological term in the service provider or enterprise network where traffic first entered from dial-up modems (yes!) in homes, or from remote branch offices. This was simply an SP network edge or an enterprise network edge without any computing capacity at the edge. They were called PoPs (points-of-presence).

The demand for application performance and content delivery required the network edge to add applications and data. Modern day Edge Data Centersfulfill that need. Content Delivery Networks (CDN) leverage them so that we get better page and video loads. This edge is now enhanced with Mobile Edge Computing, as mobile app performance needed to get better. We do it by colocating Radio Access Network (RAN) PoPs and applications.

So the old PoP got edgy with content and computing; SP edge, mobile edge, and enterprise edge came together to be the Cloud’s Edge.

The Business Edge

This is the most talked about Edge. Connected machines and people galore here. It is in our carpeted offices, in uncarpeted spaces, out in the open where we work and play. Many IoT discussions seem to presume that this is the only edge. Every IoT discussion extols the virtues of this Edge. So I’ll be brief. Mission-critical SPA goes on in this realm especially as Industrial IoT gathers momentum.

The Personal Edge

This Edge surrounds our person and is sometimes inside us. It is at home. It moves with us. Collectively this edge is mobile. The personal edge moves in and out of the business edge as we move. It comprises of home robots, glasses, smart pills, watches, home automation systems and so on. We will hear more about this edge in the next 5 years as intelligent home devices and personal devices proliferate.

Near, Far, Wherever You Are

21st century stream data processing enabled by pervasive computing and pervasive connectivity is constantly with us. We are being constantly SPA’d upon (sensed, processed, and acted upon). We will see more talk and action from players in these three edges as they innovate and adapt for new applications. As they do, remember to not let all this talk of edge computing get under your skin. It already is! Just chalk it up to proximity computing if that helps takes the edge off.

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Here is a look at how players from the world of IT and the world of OT (“operational technology”, loosely referring to industrial products and services sectors) are fishing in the venture landscape for investments and acquisitions. This has implications for you whether you are an entrepreneur, a venture investor, a corporate venture / M&A leader, or an investment banker.

The Simple World of IT acquisitions

We see acquisitions like the ones below often – a small software or hardware firm getting snapped up by an established IT player.

Countless examples of this play out across all parts of the IT stack, from network-server-storage areas to middleware to apps, data, and security. We all expect this: startups building horizontal (industry-agnostic) technology being acquired by large IT players.

Emergence of New Acquirers

Against the above historical backdrop, we’ve been seeing this new type of acquisitions by vertical-specific large and mega players. A very small sampling of them below.

The school of fish on the left is focused on applying IT to specific vertical industry or operational domain problems. e.g. wise.io for service tickets, SAIPS on AI for vision, ThingWorx for industrial IoT etc. Five years ago these ventures would still have been acquired by traditional IT players. Now there is competition for acquisitions from the industrial sectors.

The New World

The graphic below shows both the historic and new dynamic in perspective. Acquirers from quadrants 1, in addition to 2 are scouring the venture landscape, establishing outposts in Silicon Valley and other startup hubs, influencing startup direction and deal flow early, and competing with VC firms for control.

While the classic IT consumption by verticals from the traditional IT players continues (blue arrow), tech products all of a sudden find a new way to reach buyers directly through quadrant 1 vs. indirectly via quadrant 2.

Taxonomy: Small Fish and the Big Fish

Below is a generalization of the acquisition patterns and players by quadrant.

1. Big OT: Players not in high-tech sector (e.g. industrial manufacturing, services etc.) or part of their ecosystem
2. Big IT: Traditional tech players. Excludes Google, Amazon etc. who don’t fit in a particular quadrant here, but span quadrants 1 and 2.
3. Small IT: Focuses on horizontal hardware/software problems that are not industry specific
4. Small OT: Small tech players focused on industry problems. (e.g. AI for health or autonomous cars). Their technology focus could be IT or OT, but their problem domain is industry-specific (e.g. SAIPS for navigational AI, Airware in drone technology)

The Calculus of It All

Whether you are an entrepreneur, VC, corporate venture portfolio manager, or investment banker, the interplay across the players in these quadrants has become a key consideration in your day-job. For instance:

• Just as the supply of small technology firms have increased due to cloud, the potential suitors for startups have increased as well. Mature buyers from the OT world are investing in and acquiring from small OT and small IT quadrants.
• Vertical integration across IT and OT is a threat for incumbent OT players (e.g. Google in transportation and robotics, Amazon in health services) and IT players.
• Innovators dilemma problems galore in the big IT quadrant 2. Collectively, they aren’t providing or are unable to provide verticalized solutions while busy trying to stave off cloud competitors. That’s a battle on two fronts simultaneously!

Note: Apple’s acquisition of Lattice Data is another wrinkle in this whole landscape, given the way a corporate acquisition bypassed traditional VC route altogether. Lattice could have exited in quadrant 1 or 2.

The new digital trajectory of venture funding and acquisitions affects many aspects of a venture world such as:

• Product positioning: Are you simply an artificial intelligence software provider or an AI software provider for health?
• GTM: Who exactly is your buyer or channel to the end customer? Is your channel partner a vertical-specific solution provider or an IT solutions provider?
• Funding sources: Can you raise capital from traditional VC firms, corporate ventures in OT, corporate ventures in IT, or even Government?
• Potential exits: Are your suitors in the OT or IT world?

There you have it. The simplified view of the foraging and predatory habits of the various fish and its implications. It’s an exciting marine world out there!

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Managed Devices: Point-of-Arrival

Before we examine the latest arrival, a quick look at how the CPEs have evolved, for us to appreciate the progression of devices and associated services.

After we got past the early utilities like water, gas, and electricity came the phone. In the heydays of AT&T, the phone was an integral part of the network. Several lawsuits and regulations later, the phone was de-coupled from the network. That was a significant point of transition on its own. However, the arrival of the smartphone (first by Blackberry and then Apple) caused a step-change in the concept of a managed CPE.

All of a sudden, the device was being managed by several providers and users, from the telecom provider to the phone maker to enterprise IT to the end-user.

The CPE got multiple masters and still slaved well for all of them. We take this for granted today, but this change required solving many security, policy, manageability and usability issues.

The Ultimate Managed Device

Enter the ultimate managed device, the human. All those advances the phones made will be dwarfed when healthcare delivery goes digital.

We will have multiple service providers monitoring our body (or parts thereof) for cure and prevention of diseases — for example, a dietitian from India, a trainer from Russia, doctors and nurses from the country you live in, all supported by ample sprinkling of bots.

We are headed to the place where everyone of us is the CPE, the ultimate managed device.

Many trial offerings and apps perform parts of this care delivery today. A lot more technology, regulatory, and privacy issues need to be resolved to make remote delivery of healthcare a reality for the masses and achieve transformative health outcomes, but we are on our way.

Managed Devices: Passive → Active → Mobile → Alive

The graphic below shows centuries of progression of utilities and the devices. They have gone from being passive (“we simply consume stuff on tap”) to active (“we inject content back in to the utility” as with phones) to mobile (phones, cars, droids, drones) to live humans.

Humans: Datacenters in Motion

In the world of IoT, discussions center around managing fleets of vehicles, trucks, and robots or coordinating drones and droids using the cloud. We talk about cars and planes as data centers in motion. In 8 years, world population will be over 8 billion.

Can you imagine 8 billion humans, each generating more data than an airplane 24 hours a day, each processing that data through wearables and cloud, each being a datacenter on two feet?

The impact from the ultimate managed device is mind-boggling to me. What will that do to healthcare around the world and consequently human productivity?

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After several years of working in and observing the world of IoT, I have a simple formula for realizing the potential of IoT. It’s an equation: IT + OT = IoT.

The equation comes in two flavors: one suggests a necessary, but insufficient condition for success, a marriage of technologies; the other a marriage of two organizations.

Products-Services-Business-Technology

Let’s start by looking at the graphic below that shows how business leverages technology products and services using the 4-quadrant map of Products-Services-Business-Technology (PSBT). It will give us a framework to look at the implications of IoT.

The picture shows how a few decades ago, businesses bought products (phones and computers) to run their call centers. Then they outsourced call centers en masse to services companies, consuming businesses services from quadrant 1 instead of consuming products from quadrant 4. In the technology world, cloud changed the way we consume technology. Instead of buying technology products from quadrant 3, we buy cloud services from quadrant 2. This prefabrication of IT for easier consumption mirrors the prefabrication of business services in quadrant 1 that paves the way for a range of business decisions – simple outsourcing based on core vs. context decisions to evolved business models.

Can we do the same in manufacturing sector or agricultural sector? What would it look like? Stories about connected products in manufacturing are legion. So for a change, let’s look at agriculture sector and map products used in agriculture sector to the PSBT plane as shown below.

We can move from buying tractors, farming with them, and maintaining them to buying farming as a business service. i.e. Move from consumption of goods in quadrant 4, to consumption of services from quadrant 1; Do-It-Yourself farming to Get-It-Done farming, just like we saw IT move from Do-IT-Yourself to Getting-IT-Done. Outsourced labor in agribusinesses has existed for a long time due to labour shortages. So what’s new? The ability to connect the tractor to the network is new. Once you do that some application software from quadrant 2 cloud can monitor, manage, and maintain it. All of a sudden, new ways of measuring consumption and pricing based on measured consumption opens up. Voila, you have Tractor-as-a-Service powered by SaaS (quadrant 1 business service powered by quadrant 2’s IT service), complementing on-premise outsourced labour (at least until the tractor itself becomes autonomous). To top it all, this could all be paid for based on the outcome of agricultural yield or cost savings in farming, thus aligning the financial success of supplier and customer tightly.

Clearly Internet of Things is about value creation via our ability to communicate and control things over connections and automating the way we get work done. Products with embedded intelligence talking to the cloud brings the power of remote control to everyday things, much like iPhone and iCloud has done.

All of this requires information technology (IT) to be embedded in the business systems that we run our businesses on. In other words, it is operational technologies (OT) with IT inside. Ergo, IT + OT = IoT.

Are we done yet? No, we have just begun by establishing that information technology embedded in business systems opens up new services and solutions. How do we realize this in practice in our organizations where IT organizations and business operations groups and business units have historically operated not exactly in tandem? That requires another IT+OT collaboration that involves people and processes.

How organizations cross-pollinate ideas – one learning the business and looking for ways to apply IT, the other realizing IT’s potential and looking for ways to improve the business operations. This is the all-important part two of IT + OT = IoT equation.

If we get both these parts right, we can all look forward to higher levels of productivity from IT powering operational technologies and automating business operations as well as our daily tasks. That, in short, is digitization.

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