Frameworks for IoT and Networks of Ecosystems

Part 3 of 4

A framework helps visualize, categorize and analyze some thing.

Frameworks are not architectures, which are more detailed blueprints for designing, building, implementing and supporting a capability, solution, service or physical thing.

My first two blogs on #IoT discussed some of the history, scope and solutions in "What is the Internet of Things?" and then some of the categorization and amount of economic impact in "What is the Value of Autonomic Things?"

When I attended the Industrial Internet Consortium quarterly conference in Long Beach recently, my take away aligned to what I'm reading in the press, blogs, and marketing fodder:

• Lots of interesting work going on (testbeds, prototypes, new products & services)
• Lots of work still to do on interoperability and various "standards"
• Lots of nervousness around security, which, with the Sony incident, will only increase and possibly slow down some initiatives
• Lots of technical and infrastructure architecture work, but leaving data and business architectures to languish behind
• Little to no work on gaps and overlaps of the various standards bodies (vertical and horizontal) and consortiums, potentially magnifying the issues of interoperability
• Boundaries of IoT, IIoT, IoE, eieio ... are still fuzzy = big data, analytics, mobility, RFID, augmented reality, artificial intelligence, service management, ... included or parallel capabilities
• Framework(s) for most individual companies defining THEIR value (ROIC), strategy and plans are few and far between

We all remember the dot.com boom / bust and separately how RFID was going to revolutionize everything from "industrial" cargo transportation to "retail" consumer marketing, placement and sales via millions of devices on millions of products.

When the DOD, NATO and Walmart get together and say RFID is big, people take note. But the transformational revolution predicted never materialized.

There are multiple reasons why, but let me suggest the primary reason was individual companies make individual choices on individual investments and the ROIC of RFID versus competing strategic, operational and tactical opportunities and threats just didn't make the cut.

Having assisted in several RFID operational and financial evaluation studies, in most cases the business value proposition didn't exist as there were other paths to achieving the same or similar outcomes operationally and at a lower financial cost.

It's not that there are not excellent examples, outside of the M2M bits and bytes discussions, of how IoT / IoE and Networks of Ecosystems (NoE) will revolutionize individuals lives, societies, businesses and industries, rather, there still exists a lot of fuzziness on how we get there.

The question for individual companies remains:

Where is a map to the #IoT promised land or at least a framework for developing one?

So part three of my four blogs on #IoT is devoted to some frameworks that should help companies and individuals visualize, categorize and start to analyze #IoT for their company, their industry, their markets and their ecosystem(s).

Framework for the Connectivity of Things

No debate that #IoT includes connecting "things". Simple enough to frame up:

• Connectivity spectrum = one to one, one to many, many to many
• Connectivity types = Machine to Machine (M2M), Machine to Humans (M2H/H2M), Humans to Humans (H2H)

With a bit of alteration to Cisco's popular #IoE diagram, a simple framework for Networks of Ecosystems might look like this:

Framework between Products, Services and Customers

Technology vendors, analyst and consultants love TLAs (Three Letter Acronyms) for defining the purpose or focus of information technologies. MRP, ERP, CRM, eieio ...

With respect to #IoT (another TLA), let's focus the discussion to designers and manufactures of "Products" (PLM), "Services" to support those products once manufactured (SLM) and "Customer" interactions (some might call this CRM but that has a strong affinity to "sales" - so we'll use the more modern which is more applicable to #IoT = Customer Experience Management (CXM).

Let's further agree to the following:

• The Internet of "Things" resides in the "physical" world of "things"
• The physical world is real and how things "are" or "will be"
• Operational Technology (OT) is the technology of the physical world
• The virtual world is how things "should be" or simulates the real world
• Information Technology (IT) is the technology of the virtual world
• The vast majority of the internet connects Humans to Humans (H2H)
• To make things smarter we must connect things to other things (M2M)
• To make people smarter we must connect humans and things (H2M)
• To make Data smarter we must move it up the Information, Knowledge, Wisdom (DIKW) pyramid
• Without the ability to control things, smarter decisions have no effect
• The Internet of Things has the purpose of enabling people and machines to make better, faster decisions and control or act upon them

Product Lifecycle Management (PLM) covers the design, engineering, manufacturing, simulation and associated supply chain of "products" prior to their being placed in operation, use and consumption.

Service Lifecycle Management (SLM) covers the operation, servicing, engineering, maintenance, repair, overhaul, warranty, documents / content and associated supply network (new or refurbished parts) of physical things in use and being consumed.

Now, to achieve a mutually exclusive and collectively exhaustive (MECE) framework or Venn diagram, where does this leave Customer Relationship / Customer Experience Management (CRM / CXM)?

For this discussion, let's say CXM covers the capabilities and activities a seller of a service undertakes to acquire, transact and or retain a buyer of a service - AND - the interactions during the "consumption" of the operation of a product or service. This means CXM is transactional in nature and is neither virtual or physical with respect to the purpose of a products use or related services.

Controversial statement #1: The Internet of Things is a subset of Service Lifecycle events, capabilities, and activities and includes both operational and information technologies.

While the above diagram was developed in the Industrial #IoT, variations of the PLM / SLM / CXM framework is applicable to wearable or retail or consumer #IoT markets, physical products and services.

Framework for the Structure and Boundaries of Things

The structure of things follows a simple physical hierarchy with definable boundaries.

• Sensor
• Component
• System(s)
• Asset / Entity
• Assets / Fleets / Factories / Entities
• Enterprise / Domain
• Ecosystem

I believe the hierarchy of the structure of things is self explanatory with the exception of an asset / entity and an enterprise / ecosystem domain.

Assets have the connotation of inanimate objects vs. animate entities. Components, systems and domains could be biological and or societal in addition to mechanical / electrical / physical.

Enterprise is a term normally associated to a singular business or organization while an ecosystem domain could be market oriented (homes, health, P&C insurance, ...) or any enclosed network.

Framework for the Capability Maturity of IoT Analytics

The maturation of capabilities also follows a hierarchy where each level builds upon the preceding one.

• Sensing - the ability to detect and report an attribute of a thing
• Monitoring - the ability to record attributes of a thing over time and relate attributes to control parameters
• Controlling - the ability to adjust an input parameter in order to achieve a different output or outcome
• Diagnostics - the ability to diagnose or determine the cause of unacceptable conditions, performance, attributes, outputs or outcomes
• Prediction - or Predictive Analytics, is the ability to state a single future condition, attribute, parameter, output, event or outcome based upon one or more modeling algorithms, historical data, current sensor data, behavior and use.
• Prescription - is the ability to prescribe a course of action - prescriptive analytics focuses on finding the best course of action for a given a prediction and diagnosis. 
• Prognostics - the ability to prognosticate is conditional to specific prescription(s) - that is - given a prescribed course of action(s) a prognosis is the expected future state of attributes, parameters, or outputs that maintain current or new health (better or worse)
• Autonomics - the ability to automatically and autonomously control things to achieve desired outcomes

Note: Descriptive analytics is related and sometimes is even called predictive analytics but instead focuses on discovering correlations between cause and effect. Artificial Intelligence (AI) capabilities such as Machine Learning (ML) automate algorithm creation processes thus negating the need and value of static models.

Analytics also fall into embedded and remote (non-embedded) domains. For example, the oxygen sensor and on-board diagnostics computer in an automobile or the central maintenance computer on board an airplane are in the embedded sensor / analytics domain because they are "embedded" in the component, system or singular asset. The fleet management system or airplane health management system are remote to the asset thus in the non-embedded domain.

In some cases the data and processing to enable the next capability maturity level can be achieved without fully exploiting or optimizing the lower level. In some cases, the value of a lower capability maturity level is lessoned accordingly but not always depending upon the desired outcomes of the "thing".

For instance, diagnostics of a component or system within an asset or entity can be "calculated" without fully automating a control system. But the full value of diagnostics, prognostics or autonomics can not be optimized for a system, asset/entity, enterprise or ecosystem without some degree of non-manual control.

Frameworks for Vendor Landscapes

There are a plethora of #IoT landscapes posted on the internet right now. Some interesting ones are listed below:

• The Wearables Wheel: A visual map of the wearables landscape
• The Internet of Things Ecosystem - Convergence of Big Data and IoT
• Making Sense Of The Internet Of Things Landscape
• The Internet of Things Protocol Landscape
• Harbor Research - M2M Industry Landscape
• M2M World of Connected Services - IoT Landscape

Shivon Zilis recently shared her analysis on "The Current State of Machine Intelligence" diagraming a framework for categorization of vendors and their placement within the machine learning and artificial intelligence landscape.

it’s much easier to identify crowded areas and see white space once the landscape has some sort of taxonomy.

As opposed to the technical, data or industry "architectural" approach most of the landscape authors used in the list above, Shivon included "intention" categories like Rethinking Industries & Rethinking Enterprises.

Landscape frameworks like Shivon's make you really contemplate how one is analyzing markets and vendors.

Some of the questions that arose for me after reading Shivon's landscape were:

• Is "Diagnostics" a "Rethinking Industries" vertical or a "Core Technologies" horizontal?
• Does diagnostics include sensing, monitoring and or controlling?
• If prognostics is part of "Predictive APIs" where does diagnostics stop and prognostics start, since they are related algorithms?
• Where is Autonomics?
• Where is aerospace, aviation and defense industries - who have been at the forefront of #IoT for well over a decade?
• In "Rethinking the Enterprise" where is PLM, SLM, SCM and does "Sales" cover both CRM and CXM?
• Are "wearables" part of "Rethinking Humans Capital Management"?
• Where do you place SmartSignal, Osys, Verizon Telematics?

For individuals or companies or consortiums looking to advance their #IoT development, these "landscape" diagrams can be helpful for global open mass peering and collaboration (wikinomics).

Frameworks for Strategy Development

I think it is fair to say for most markets and companies, IoT is a blue ocean, as defined by Chan Kim and Renée Mauborgne. For those in the aerospace industry, where #IoT capabilities have led to new business models that now account for over 50% of revenue and upwards of 70% of profits, there is little doubt on the color of the ocean.

Strategy development can be broadly categorized into two approaches:

• Strategy as War (rivalry, competition, e.g., Porter's Forces model)
• Strategy as Love (customer bonding, e.g., Hax's Delta model)

Both are valid and in combination deliver superior business strategies.

IoT Competitive Strategy

The dean of competitive strategy, Michael Porter co-authored with Jim Heppelmann, CEO PTC, an excellent article on, "How Smart, Connected Products Are Transforming Competition."

Since I don't have permission to reuse any of the Harvard Business Review content and don't have a lot to add to their excellent thesis and points, I'll leave it to the reader to review their HBR article.

Actually, I do have one little point to make:

Controversial statement #2: There are no such "things" as products, there are only services.

I first made this statement publically in 2004 about the same time Marc McCluskey coined the term Service Lifecycle Management at AMR and I defined SLM in an article for Aircraft Technology Engineering & Maintenance magazine. We had been using the term internally at Accenture for almost two years after developing eleven SLM enabling patents.

The "a-ha" moment for me came at one of Dr. Morris Cohen's annual Service Management Leadership conferences at Wharton, when Michael Capellas (CEO MCI at the time and ex-CEO Compaq) profiled Dell Computer, arguably a "product" company. Of the seven main activates Dell performed, only one - computer assembly - could remotely be considered a non-service process.

I'm not actually sure how "controversial" the statement is anymore, in a world of Software-as-a-Service (SaaS), Infrastructure and Platform (IaaS & PaaS), with aerospace engine OEMs selling engines "the razor blade product" bundled with financing, logistics and engineering services denominated in pounds of thrust consumed and with "servitization" becoming more well-known and embraced across many other industries.

Everything spoils. This is a core concept of pricing and revenue optimization in the travel, transportation, logistics and retail industries. Physical things exists to deliver a service that is consumed. (e.g., smartphones deliver telecommunications, automobiles deliver transportation (taxi, rental, lease, ...), MRI machines deliver images for health diagnostics and prognostics, wearable watches deliver health data and trends, ...).

Use a physical "product" for the "service" it was designed to deliver or the service and the value of the "thing" spoils.

For the world of IoT, where the name includes "things" (which could confuse people into focusing on the physical products), it is critically important for companies to build their strategy and business models (pricing & revenue optimization, marketing, operations, finance & accounting, ...) fully understanding and embracing servitization and the service lifecycle coupled to customer's experience.

In a forthcoming blog, I'll go into more detail servitization, SLM and the differentiation of business and revenue models relative to traditional "product" models.

IoT Bonding Strategy

Many companies and organizations develop competition based strategies focused on providing the "Best Product / Service" via quality, speed and, or price.

The "bond" between a provider and a customer or end consumer based upon a "Best Product / Service" strategy is weak, that is, find a like product / service at a lower price and the customer switches.

Apple computers, on the other hand, are not low price, have fewer software applications than PCs, yet have a very devoted (bonded) clientele because they deliver simple Total Solutions that consumers are willing to pay a premium for.

I doubt anyone has said MS Windows is a better, faster, cheaper operating system relative to a plethora of alternatives, yet the Win-Intel combination is highly bonded to the PC operating system sub-market because of Systems Economics.

Arnoldo Hax and Dean Wilde conducted an "a posteriori" multi-year study of companies strategies and success called "the delta project". If you layout their delta model (Greek "D") horizontally, you get a framework for strategic positioning as a function of customer bonding to services versus industry or market structure as seen below.

While the book, "The Delta Project: Discovering New Sources of Profitability in a Networked Economy" circa 1999 is a bit dated in its examples, its main points are spot on for #IoT and #NoE. Another good reference is still Dean & Company's website on Customer Bonding and Strategic Positioning.

The point for companies pursuing IoT initiatives is the alignment of a firm's capabilities to the highest possible customer bonding strategic position achievable. If that cannot be achieved singularly, then the question arises, who should you partner, merge or acquire with to achieve it?

One short comment on the topic of financial engineering that I believe is also critical to #IoT initiatives. Financial engineering crosses the domains of Strategy and Business Architecture.

IF an organization pursues a bundled services, total solutions, or systems economics strategic position then the pricing, contracting, accounting and cash flows of a "services" business model are significantly different than in "products".

Anyone in the XaaS business or performance based logistics or power by the hour business has lived these significant differences in finance and accounting. So while the payoff can be considerable (one "product' OEM reported 28% of revenues from services was generating 67% of net profits), the cash flows and liabilities are not so straight forward.

From Frameworks to Architectures

An architecture is a blueprint and plan for building something that has a well defined purpose. Frameworks are not architectures, but lend themselves to understanding that can help advance architecture development.

Enterprise Architecture is a mature and well developed multi-discipline approach to organizational planning and change. The views of EA are:

1. Strategy Architecture
2. Business Architecture
3. Solutions Architecture
4. Data Architecture
5. Technical Architecture

I purposefully placed these in the order in which they "should" be sequenced, however, as most innovations go, the reverse order is commonly how they "are" sequenced - starting with a disruptive technology that needs data to deliver solutions and then opens up new business markets and opportunities that need financing and, if big enough, necessitate well defined strategies.

Future blogs, by myself and others will delve into the details of all of the architectures (and standards) needed to deliver #IoT for companies and markets.

Looking at the various landscape diagrams that have been created over the past year, it is obvious that:

• #IoT blue ocean markets are quickly becoming red from the number of startups and established company initiatives and partnerships,
• that the hype of trillions of devices and trillions of dollars that have driven hundreds of millions of dollars in investment is still accelerating
• that this peak of inflated desires and expectations will turn to fear (of actions and of inaction and of unintended consequences), starting with the Porter / Heppelmann HBR article
• that prosumer winners and losers are going to quickly start falling out
• and that M&A in the various #IoT markets (horizontal and vertical) will accelerate in 2015.

In the forth and final installment, I'll spend some time discussing what needs to be done to break down barriers to IoT adoption,what comprises IoT Networks of Ecosystems or "Halos" and how IoT is closing gaps in the PLM, SLM, CXM spectrum and Why IoT needs to be Servitized to accelerate its Tipping Point.

Part 1: What is the Internet of Things IoT?

Part 2: What is the Value of Autonomic Things in IoT?

Part 4: Why IoT needs to be Servitized to accelerate the Tipping Point in a Sharing Economy (or: how servitization accelerates and broadens IoT sales)