Assuring Your IoT Objectives are Funded by Delivering Business Value

D. Brancato

Chief Technologist/Enterprise Architect

Microfocus – Vertica

Tallinn, Estonia

8-FEB-2108

Please note that many users and orgs make this deck possible, including and not limited to Gartner, Gizmodo, O’Reilly & Associates, The Open Group, HP and IBM, Microfocus, and many IoT practitioners globally. Thank you!

I have never had a creative thought in my life. Everything I think and do, is because I copied it from history, the Web, coworkers, teachers, passengers on public transportation – oh, and you, and my wife and kids.

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What We will Cover This Morning– A Synopsis

1. Business leaders today are tasked with delivering near real-time value to global markets faster and more reliably than ever before.

2. The harvesting of sensor, IoT and IIoT devices, requires an solving for latency, interoperability, and costs to assure business value.

3. The data driven enterprise requires right, light, and liquid data, correlated to value, to business strategy, to assure enterprise governance. Compare to bigData and infrastructure costing.

4. Smart Cities, connected cars, and factory OT require sustainability.5. Interoperability is the biggest roadblock to IoT universal acceptance.6. Your IoT project must deliver business value, traceable to business

strategy and outcomes.

An examination of components to deliver business value is presented.

Who am I?

▪ Former Army solider, merchant mariner, arctic logistics expertise

▪ Aviation/aerospace degrees

▪ Modeling and simulation practitioner

▪ Enterprise architecture skills and consulting

▪ Volunteer: Open standards author (opengroup.org), rocket/space advisory (archmission.com), bIoTope Smart Cities (Brussels, Lyon, Helsinki) advisory

▪ Help clients imagine, engage, solve with Vertica - a columnStore and analytics engine, supporting IoT/IIoT - globally

▪ Married, live in Seattle, USA, on a boat – raised 7 kids

HPE Confidential | Share under NDA

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The Digital Mesh is beginning: a cooperative, portable, interoperable ontology of taxonomically organized reusable, valuable data

What is the Internet of Things?

“The Internet of Things is the network of physical objects that contains embedded technology to communicate and sense or interact with the objects' internal state or the external environment…

• with capabilities increasingly seen as independent, autonomous.• with an increasing demand for interoperability with other ‘things,’ often heterogeneous

in nature.”

Consumer “Things” - IoT

Personal sensing with remote monitoring and control – Fitbit, Nest,

smart refrigerators, etc.

Industrial “Things” (IIoT)

From individual sensors to entire power plants – the world of Operational Technology (OT)

Is Your IoT Work Traceable to Business Strategy?

Review: How does Business Work in 6-Steps

▪ Global Events and Drivers, defines ->

▪ Strategy: Verb + Noun + Time + Percent Increase/Decrease, requires ->

▪ Capabilities, required by ->

▪ Organizational Chart: Humans, Systems, Machines, assured by ->

▪ Governance: Proves that the work done was ‘traceable’ to Strategy, sustained by ->

▪ Improve, Sell, or Shutdown

▪ Define Strategy (previous slide)

▪ Define Value: money or work-delivered, both?

▪ What happens when you, as technology leaders, don’t have access to a business strategy?

▪ Force it. Use Capability Modeling to describe the capabilities that exist in your org from the highest levels, down to the data models that IoT uses to deliver ‘value’ up the stack.

▪ Archi. https://www.archimatetool.com/download

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Strategy Defines What is Funded

Open Systems Architecture Vision Using Archi

▪ Most orgs have 6-8 capability levels from executive capabilities to tactical capabilities.

▪ Often, Value Models or Chains, are a part of showing, supporting proof of the efficiencies of the enterprise.

▪ Consider IT4IT, a value model for IT.

▪ T-Mobile, Boeing, Microsoft, HP, and hundreds of other orgs use the model to assure the right capabilities exist to support business strategy.

▪ IoT and it’s capabilities likely show up around L6-8.

▪ When IoT capabilities are not ‘spelled’ out explicitly, can you expect executives to fund what they cannot see?

▪ Sample metrics are often included with the capability model as a Traceability Model – 3 column Excel: named capability, sample metrics to prove the capability, and field with an index like ‘Sell->Products->Dev Solutions->Assemble Solution>Install Solution->Measure/Report Sensors->Govern/Maintain IoT

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Sample L0/L1 Capabilities

Use Stories to Sell your IoT Vision

▪ If you don’t do this, who will?

1. Know your message

2. Find the right example

3. Weave your narrative

4. Convey passion

5. Support with facts

▪ Want a great story?

▪ Kevin Ashton has told the world that in 1999 he invented the Internet of Things. In 1998, a Finnish inventor and educator saw a need to track airport equipment in Helsinki. He created sensors to map locations of the airport equipment, and along with it, created two patterns - standards, he donated to the Open Standards community…

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Stories are How the Digital Era will Mature

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Use Roles in Your IoT Stories

▪ Roles personalize capabilities.

▪ APQC (American Productivity & Quality Center) helps organizations work smarter, faster, and with greater confidence. It is the world’s foremost authority in benchmarking, best practices, process and performance improvement, and knowledge management. APQC’s unique structure as a member-based nonprofit makes it a differentiator in the marketplace. APQC partners with more than 500 member organizations worldwide in all industries. With more than 40 years of experience, APQC remains the world’s leader in transforming organizations.

▪ APQC's Process Classification Framework®(PCF) is the most used process framework in the world. It creates a common language for organizations to communicate and define work processes comprehensively and without redundancies. Organizations are using it to support benchmarking, manage content, and perform other important performance management activities.

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APQC.org and Roles to Deliver ValueGet Use Cases here! Backbone of HRBOK

▪ Roles personalize capabilities.

▪ Humans, systems, and machines perform roles.

▪ IoT existence (e.g., a smart car or vacuum cleaner) is reported as Health, Performance, Capacity

▪ IoT instantiations report metrics associated with their intended use, or capability.

▪ Report to your organization, the IoT capabilities you deploying, their metrics, and the roles who require these capabilities

▪ Example: Manufacture Axle Housings, Test Material Density (using IoT infrared sensors), Report Material Metrics, etc.

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An IoT Capability has Metrics

“Today, less than 0.5% of all data is ever analyzed & used.” (Gartner, 2017)

▪ Imagine the potential for data savings… if you size your IoT projects to data that generates business value!

▪ Imagine if you gave up on big data, and focused on the right data, data that represents the answers to business questions

▪ Note. Data and analytics teams spend far too much time on data collection, getting ‘all the data’ instead of the ‘right data,’ rather than understanding and prioritizing business problems to apply machine learning (ML). The growing volume of unused data increases anxiety, unrealistic hopes that ML will be a quick-to-value story. Remember: train staff, teach clients -> it takes 12-18 months to build a data analytics team.

Use Enterprise Architecture Principals

▪ Enterprise Architecture is the practice of assuring the governance of capabilities that trace to business strategy existing over the business ecosystem. EA often owns ‘go/noGo’ in terms of capital acquisition, and always owns governance.

▪ EAs may use frameworks like FEA, DODAF, TOGAF, MODAF, reference models, and others to create roadmaps, artifacts, and deliverables. Traceability to business value is their trademark.

▪ If the goal is executive sponsorship and enterprise visibility, use an EA. EAs are often involved in working with public demand in smart cities (compared to business demand in a traditional business).

▪ 15-20% of EAs report to the CIO, and the rest report to COO, CFO, CEO, Chief Business/Marketing Officer.

▪ EA is about getting out into the enterprise, and not just IT with data practitioners. The rewards are greater, and the risk is higher. Correlation is not causation is assured by getting out and looking!

Using EA with IoT Pursuits

Use Open Standards in Your Design

IT4IT™ is an IT integration model industry standard

▪ Manage IT as an end-to-end value chain

- It’s about the end user consumption experience

- It’s not about the technology!

▪ Tightly manage the data and functions across the service life cycle

▪ This is an industry first!

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to run the business of IT in a digital enterprise

IT Value Chain IT Reference Architecture“normative”“guidance”

describes the structure of IT management prescribes the functional & information architecture

IT4IT™ is a trademark of The Open Group

Efficiency

&

AgilityFinance & Assets

Intelligence & Reporting

Resource & Project

Governance, Risk & Compliance

Sourcing & Vendor

IT V

alu

e C

hain

Plan Build Deliver Run

Service Model Backbone

Using IoT Open StandardsO-DF, O-MI, O-DEF, Open Platform 3.0

IoT Metrics, Again, and then Standards…

IoT metrics must assure:

▪ Least Cost.

▪ Lowest Latency.

▪ Interoperability of heterogeneous IoT.

▪ Lastly, wrap the IoT names and their supporting metrics in a capability and report to Executive Team. Test them! They are selling your work!

▪ Report the Open Standards use to brand the solution as ‘best of.’

▪ Why Open Standards?

IoT Today – as by Independent Vendors

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▪ Sensor data pushed to virtual/real servers

▪ Data collected into vertical silos

▪ M2M communication limited to local network

©The Open Group 201521/4/2015

Systems of Systems

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System?System?

System?System?System?

System?

System?

System?

System?

IoT with Open Group Standards

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▪ Systems rather than sensors

▪ Horizontal integration as easy as vertical integration

▪ Connections created without programming as needed

▪ Establish two-way, time-limited information flows between trusted entities and the physical product(s)

Systems of Systems:Open Platform 3.0 Use Cases

Red connections: O-MI & O-DF

Systems of Systems: Closed-Loop Lifecycle Management (CL2M)

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Instance

Manufacturing 1Manufacturing 2

User 1

User 2

Recycling

InstanceInstance

Instance

InstanceProduct information

Where? In one or many places?

Type/version/instance-specific?

Information

queries/updates

Designer 1

Designer 2

”Thing”

”Thing”

”Thing”

Business

idea/plan

IoT

▪ Lifecycle view: IoT is about managing all information about any product/Thing

▪ Information is Distributed over Systems (devices, servers, applications, ...)

▪ Information is Distributed over Organizations (companies, individuals, authorities, …)

▪ Product (and its parts) are uniqueinstances

▪ How manage identities, access rights, …?

▪ IoT should provide necessary Capabilities for CL2M

Red arrows: O-MI & O-DF

Standards of Open Platform and IoT Work Group

▪ Published by The Open Group on October 16th, 2014

▪ Open Messaging Interface (O-MI): communication

▪ Open Data Format (O-DF): payload

▪ May be used independently of each other (as HTTP and HTML)

▪ Publish available information and services

▪ Discover availableinformation and services

▪ Read/write of immediate and historical information, alerts, other events, …

▪ Subscribe to information using Observer Design Pattern

▪ Specified using XML schema

▪ Can be transported by ”any” underlying protocol: HTTP, HTTPS, FTP, SMTP, XMPP, file transfer, USB sticks, plain sockets, …

▪ Usable as Standardized IoT REST API as well as M2M, M2S etc.

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Format

XML,XML schema, JSON,HTML

O-DF

OSI ModelLower Layers

Communication

HTTP(TCP/IP, SOAP, SMTP, …)

O-MI

Web

Application

Ap

plic

atio

n L

ayer

IoT

Many Things, Many Ontologies: InteroperabilityLet’s Play the ‘Fund My IoT Project’

▪ The game.

▪ The device.

▪ The money.

▪ Many Data Model and API Problem. 60-80% of bigData/IoT projects spend their time on data engineering/conversion.

▪ What a problem! And the fix?

▪ Common industry, organization, or product ontologies or data models.

▪ This is the next chapter of IoT!

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Most Common IoT Plays: Event Correlation and Predictive Maintenance

▪ Given a digital device, logs are often created that detail application and system events over the lifecycle of an object.

▪ Given many objects in an ecosystem, using a colStore as a syslog or enterprise correlation engine is desirable.

▪ There are log standards (OWASP, NCSA CLF, etc.), enabling events to be correlated by type, dataTime, and location. Log interoperability is troublesome in heterogenenousenvironments. EAs may require log standards to be complied with (e.g., Home Depot’s ‘building permit’ concept).

▪ Install IoT device, include location of colStore syslog or ESB, publish/subscribe. Use queries to sort/bubble events over time. Find cause, often first named, and created service incident.

▪ Boeing has about 100k ITSM tickets per month and millions more events. A colStorecan be a valuable component to solving for root cause in a complex, multi-location, multi-vendor, multi-device ecosystem. The Open Platform 3.0 standard specifies event correlation as a capability of the standard.

Event Correlation: Improve Time-to-Value

▪ Often seen as an OT play, predicting pattern evolution and confidence intervals over time is a Vertica play.

▪ Given many machines in a factory, with many data models and locations, understanding maintenance models and intervals leads to savings. It’s competitive/hard, req’stime. M2M, M2DL, M2P, M2A.

▪ 23andMe and the questions after you buy the product? They are attempting to predict your longevity/healthfulness by your lifestyle patterns. Work with text solutions to forecast likelihood of events occurring in the future. M2A, with the M == you.

▪ Vertica may be a component to a paired offering of wideData to narrow reporting – see HPE EG’s Purdue UnivSoundScape. M2A.

▪ Remember, one row per subject is a wideStore attribute, but given trillions of people, a colstore is required to address the limited patterns that a widestore describes. Lookup.

▪ Look for healthcare and lifestyle startups matching behaviors, patterns with results, goals.

Predictive Maintenance: Min Cost of Operation/Life

IT

OT

Policy Governance

Enterprise Event Correlation and Maintenance Management Prediction Conceptual Model

ERP, EAM, Analytics/Reporting Solutions

Application/ServiceService CatalogHumans, Systems,

Machines, IIoTUsingBusiness CapabilityStrategy Solved by Solved by

OLA to Service

SLA to User

A gap in delivered expectation is an event – variance in negotiated quality, cost, latency/speed. OLA metrics are a child of service demand SLA metrics. Governance identifies responsible human, system, machine, IIoT OLA failure. OT uses 8-10% of generated data, and residual data is rarely delivered as business value. Collecting and deriving usage patterns over time enables event correlation and maintenance management pattern modeling to lower OT costs and trace to business value (e.g., vendor selection/partnering, least cost production, etc.). Collecting discrete measures (i.e, ID, location, machinePosition (x, y, z)) is a best case, demonstrating least latency, best time-to-value business case, and implementation velocity.

MES

SCADA

PLC MC IPC

Gateway(s)Data Aggregation

(Historian)

Graphic represents IIoT as might be found in a factory floor, compared to IoT and the consumer market (e.g., Fitbit, Nest, connected refrigerator or scales). --db

Enterprise Event/Data Aggregation

1:m Historians (Vertica) and a single Enterprise Correlation/Data Aggregation Store

Enterprise ITGeographical Information System (GIS)

Client Role

Tower ID 2

Data Source

Data Source

Data Aggregator

Data Source

Tower ID 1

Data Source

Data Source

Data Source

Required Capability Planning/Modeling

Business CapabilityStrategy

EdgeGateway(s)

Data Aggregator

Value-Add Algorithms

Curated DataOver Fiber

Fiber

Tower Cluster:Tower ID 10-50

Data Sources

Data Sources

Data Sources

Data Aggregator

Fiber

CRM

BPM

Web(Service Catalog)

Visualization Solution

Map Store

Analytics Datastore

Enterprise Data Warehouse +

Analytics

Data Aggregation (Insert)

Machine Learning

Tower ID 2

Data Source

Data Source

Data Aggregator

Data Source

Tower ID 1

Data Source

Data Source

Data Source

Unsupervised Learning

ClusteringSimilarity

EdgeGateway(s)

Data Aggregator

Phase 1

Curated DataOver Fiber

Fiber

Tower Cluster:Tower ID 10-50

Data Sources

Data Sources

Data Sources

Data Aggregator

Fiber

Supervised Learning

Phase 2

Classification

Estimation

Binary (Y/N, M/F)

Ordinal Comparison

(s, m, l)

Categorical(white,

blue, red, black)

Numeric Calcs(best angle, price, traffic propagation/

time)

Enterprise Data Warehouse +

AnalyticsRight Data / Fit for Use

Note. Outputs (extreme left and right) are outcomes for the Data Aggregation

capability.

[Trace to Strategy]

Pull these Components Together: Enterprise ArchitectureUsing an EA Roadmap to Include Your IoT Deliverable or Solution

▪ Enterprise architecture (EA) is a discipline for proactively and holistically leading enterprise responses to disruptive forces by identifying and analyzing the execution of change toward desired business vision and outcomes. EA delivers value by presenting signature-ready recommendations for adjusting policies and projects to achieve target business outcomes that capitalize on relevant business disruptions.

▪ Further, showing that strategy traces to roles and capabilities that solve strategy, using data as the answers to business questions.

▪ A EA is a plan of attack, a roadmap of capability that traces ‘up’ to strategy, and ‘down’ to products or solutions – which are processes, applications, or services.

▪ Time to Value is Critical. RightData over BigData to demonstrate how IoT delivers business answers to strategic solutions now.

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Blockchain and IoT: Future-State Disruptors

Blockchain and the Other EconomiesWhat is It, and Why It Matters to IoT Leaders.

▪ Blockchain. Public-ledger that no single person controls, allows companies and individuals to collaborate with trust, transparency. It’s open source, cryptographically secure. Often associated with bitcoin. Look for post-Etherium blockchain vs BitCoin versioning.

▪ Gap. 2B folks without a bank account or infrastructure, and no hope it getting one. 14% of world lives on less than $2 USD/day. Capitalism is not sourcing to this community. Mobile payments - IoT is getting there by reducing cost, latency, interop of transaction.

▪ Market. Global. I attended Blockchain Santa Clara last week – 15k attendees day-1. IoT to IoT, IoT to consumer to consumer to cloud, etc.

▪ Use to Date. IBM has a product, DoD has it in use in certain weapon systems to secure supply chain, cryptocurrencies rely on it, movement by China/India/Africa ref micro/nano payments for retail, certain ‘sharing communities.’

▪ Risk. SHA-256 with 32-byte hash. 2nd biggest PKI on Earth behind DOD CAS. Little risk security-wise.

▪ Should You Care? Opinion: if bitcoin is a $10,000 $5,000 fad, it’s nonsense. Best read is Don Tapscott’s“Blockchain Revolution,” and check out safarionline for courses. Best guess to commodity is 10-years.

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Summary:• Assure cost, latency, interoperability • Tell stories• Use EA and Capability Modeling• Use Open Standards• Model, then reference architecture, repeat• Blockchain and mobile payments• Use Vertica for ‘big’ narrow data/metrology

.Download the community edition:https://my.vertica.com

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Geospatial Real-Time Text Analytics

Event Series

Pattern Matching

Time Series

Machine Learning

Regression

Messaging

Data Transformation

ETL

BI & Visualization

R Java Python

USER DEFINEDLOADS

User-Defined Functions

C++

ODBCJDBCOLEDB

SQL

External tables to analyze in place

Security

User Defined Storage

An Open Architecture Integrated with Rich Ecosystem

Don.Brancato@Microfocus.com@Don_Brancato