Hippo: IoT-based paradigm shift from passive to active insurance companies

I’m a big advocate of incremental IoT strategies (check out my recent webinar with Mendix on this approach), for existing companies that want to test the waters first. However, I’m enough of a rabble-rouser to also applaud those who jump right in with paradigm-busting IoT (and big data) startups.

Enter, stage left, a nimble (LOL) new home insurance company: Hippo!

IMHO, Hippo’s important both in its own right and also as a harbinger of other startups that will exploit the IoT and big data to break with years of tradition in the insurance industry as a whole, no longer sitting passively to pay out claims when something bad happens, but seizing the initiative to reduce risk, which is what insurance started out to do.

After all, when a Mr. B. Franklin (I’ll tell you: plunk that guy down in 2017 and he’d create a start-up addressing an unmet need within a week!) and his fellow firefighters launched the Philadelphia Contributionship in 1752, one of the first things they did was to send out appraisers to determine the risk of a house burning and suggest ways to make it safer.

Left to right: Eyal Navon, CTO and cofounder; Assaf Wand, CEO cofounder of Hippo

In fact, there’s actually a term for this kind of web-based insurance, coined by McKinsey: insuretec” (practicing what he preached, one of Hippo’s founders had been at McKinsey, and what intrigued the founders about insurance as a target was that it’s a huge industry, hasn’t really innovate for years, and didn’t focus on the customer experience.).

I talked recently to two key staffers, Head of Product Aviad Pinkovezky and Head of Marketing, Growth and Product Innovation Jason White.  They outlined a radically new strategy “with focused attention on loss reduction”:

  • sell directly to consumers instead of using agents
  • cut out legacy coverage leftovers, such as fur coats, silverware & stock certificates in a home safe) and instead cover laptops, water leaks, etc.
  • Leverage data to inform customers about appliances they own that might be more likely to cause problems, and communicate with them on a continuous basis about steps such as cleaning gutters that could reduce problems.

According to Pinkovezky, the current companies “are reactive, responding to something that takes place. Consumer-to-company interaction is non-continuous, with almost nothing between paying premiums and filing a claim.  Hippo wants to build must more of a continuous relationship, providing value added,” such as an IoT-based water-leak detection device that new customers receive.

At the same time, White said that the company is still somewhat limited in what if can do to reduce risk because so much of it isn’t really from factors such as theft (data speaks: he said thefts actually constitute little of claims) but from one, measured by frequency and amount of damage (according to their analysis) that’s beyond their control: weather. As I pointed out, that’s probably going to constitute more of a risk in the foreseeable future due to global warming.

Hippo also plans a high-tech, high-touch strategy, that would couple technnology with a human aspect that’s needed in a stressful situation such as a house fire or flood. According to Forbes:

The company acknowledges that its customers rely on Hippo to protect their largest assets, and that insurance claims often derive from stressful experiences. In light of this, Hippo offers comprehensive, compassionate concierge services to help home owners find hotels when a home becomes unlivable, and to supervise repair contractors when damage occurs.”

While offering new services, the company has firm roots in the non-insuretech world, because its policies are owned and covered by Topa, which was founded more than 30 years ago.

Bottom line: if you’re casting about for an IoT-based startup opportunity, you’d do well to use the lens McKinsey applied to insurance: look for an industry that’s tradition-bound, and tends to react to change rather than initiate it (REMEMBER: a key element of the IoT paradigm shift is that, for the first time, we can piece “universal blindness” and really see inside things to gauge how they are working [or not] — the challenge is to capitalize on that new-found data). 

Creating Your Incremental IoT Strategy Webinar Tomorrow!

Posted on 1st May 2017 in circular company, data, design

creating your IoT strategy webinar

Hope you’ll join me and Mendix  (which, BTW,  Gartner just tabbed as a platform as service [Paas] “Magic Quadrant” leader for its low-code tools for rapid app development!), for a 10 AM (EDT) webinar Tuesday the 2nd on creating incremental IoT strategies (register here).

In a way, this is an update of the e-book I wrote for SAP several years ago, Mastering the Internet of Things Revolution, in which I also outlined an incremental strategy for testing the IoT waters and then building on those early experiments for more comprehensive change.

That’s important if your company doesn’t have the resources for a total IoT makeover, or if you’re a little in doubt about how the IoT would benefit you.

While I do give a teaser for my IoT-data based “Circular Company” paradigm shift, the webinar is otherwise focused on how incremental IoT projects allow you to build unprecedented (and previously impossible, due to our inability to “see” what was happening inside of things) precision in every aspect of your operations:

Along the way I’ll show how the Mendix platform can play a role, — consistent with the democratizing data meme I’ve pushed since my Data Dynamite book — of empowering everyone, not just programmers, to quickly create enterprise low-code apps to capitalize on the incredible data the IoT yields.

Please join us.

 

Live Blogging Gartner ITxpo Barcelona!

After a harrowing trip via Air France (#neveragain) I’m in lovely Barcelona, live-blogging Gartner ITxpo courtesy of Siemens — but they aren’t dictating my editorial judgment.

Keynoter is Peter Sondergaard, Sr. VP, Gartner Research:

  • start with high-scale traditional IT structures, but with new emphasis on cloud, etc. IT system now partially inside your org. and part outside.  We are half-way through transition to cloud: half of sales support now through cloud. More financial, HR & other functions. General trend toward cloud, but still some internal processes as necessary. Must clean up traditional inside processes.
    • “Ecosystems are the next evolution of Digital”
    • Must learn to measure your investments in customer experience.
    • Starting to explore VR & AR (personal shout out to PTC & clients such as Caterpillar!!)
    • must understand customer’s intent through advanced algorithms.  Create solutions to problems they don’t even know they have!
  • next domain of new platform: Things:
    • build strategies with two lenses: consumer preferences, AND the enterprise IoT lens.
    • leverage exponential growth in connected things
    • 27445 exabytes of data by 2020!
    • can’t just bolt on new systems on old ones: must rework existing systems to include devices — processes, workflow, much harder (i.e., my circular company paradigm).
  • intelligence: how your systems learn and decide independently
    • algorithms– algorithmic intelligence — drives decisions
    • now, AI, driven by machine learning. Machines learn from experience.
    • information is new code base
    • we will employ people to train things to learn from experience through neural networks
  • ecosystems
    • linear value supply chains transformed to ecosystems through electronic interchange.
    • others can build experiences, etc. that you haven’t thought out through APIs  — my “share data” Essential Truth. APIs implement business policies in the digital world.c
  • customers
    • customer driven

Where to start?

  • 70% of IoT implementation is through new organization within companies!

Now other Gartner analysts chime in:

  • insurance: engage your customers.
  • smart gov: must interact with those who implement. Must re-imaging public involvement sense/engage/interact
  • case study: Deakin University in Australia: digital platforms to enhance student experience.
  • case study: Trenitalia mass transit system switching to predictive maintenance! Huge cost savings. “Experience hands & beginners mind at work” — love that slogan!!!! “Listen to the train instead of scheduling maintenance”
  • blockchain: ecosystem, brilliant in simplicity. All can see transaction but no one can invade privacy. Use to solve many problems: data provenance, land registry, public infrastucture, AI.
  • Woo: use this to TRANSFORM THE WORLD!!!
  • ratz — I was preoccupied at time, they talked about a new mobility system for seniors — re my SmartAging paradigm!!
  • paradigm shift — partnering with competitors (much of what I wrote about in DataDynamite: share data, don’t hoard it!)  Think about Apple & Google driving car companies’ interfaces. “Do you join hands with digital giants or join hands with them?”).
  • ooh, love the digital assistant correcting his presentation. I can only dream of a future where there are millions added to grammar police!

 

 

Circular Company: Will Internet of Things Spark Management Revolution?

Could the IoT’s most profound impact be on management and corporate organization, not just cool devices?

I’ve written before about my still-being-refined vision of the IoT — because it (for the first time!) allows everyone who needs instant access to real-time data to do their jobs and make better decisions to share that data instantly —  as the impetus for a management revolution.

My thoughts were provoked by Heppelmann & Porter’s observation that:

“For companies grappling with the transition (to the IoT), organizational issues are now center stage — and there is no playbook. We are just beginning the process of rewriting the organization chart that has been in place for decades.”

If I’m right, the IoT could let us switch from the linear and hierarchical forms that made sense in an era of serious limits to intelligence about things and how they were working at thaFor companies grappling with the transition, organizational issues are now center stage—and there is no playbook. We are just beginning the process of rewriting the organization chart that has been in place for decades.t moment, to circular forms that instead eliminate information “silos” and instead give are circular, with IoT data as the hub. 

This article expands on that vision. I’ve tried mightily to get management journals to publish it. Several of the most prestigious have given it a serious look but ultimately passed on it. That may be because it’s crazy, but I believe it is feasible today, and can lead to higher profits, lower operating costs, empowering our entire workforces, and, oh yeah, saving the planet.

Audacious, but, IMHO, valid.  Please feel free to share this, to comment on it, and, if you think it has merit, build on it.

Thanks,

W. David Stephenson


The IoT Allows a Radical, Profitable Transformation to Circular Company Structure

 

by

W. David Stephenson

Precision assembly lines and thermostats you can adjust while away from home are obvious benefits of the Internet of Things (IoT), but it might also trigger a far more sweeping change: swapping outmoded hierarchical and linear organizational forms for new circular ones.

New org charts will be dramatically different because of an important aspect of the IoT overlooked in the understandable fascination with cool devices. The IoT’s most transformational aspect is that, for the first time,

everyone who needs real-time data to do their jobs better or
make better decisions can instantly 
share it.

That changes everything.

Linear and hierarchical organizational structures were coping mechanisms for the severe limits gathering and sharing data in the past. It made sense then for management, on a top-down basis, to determine which departments got which data, and when.

The Internet of Things changes all of that because of huge volumes of real-time data), plus modern communications tools so all who need the data can share it instantly. 

This will allow a radical change in corporate structure and functions from hierarchy: make it cyclical, with real-time IoT data as the hub around which the organization revolves and makes decisions.

Perhaps the closest existing model is W.L. Gore & Associates. The company has always been organized on a “lattice” model, with “no traditional organizational charts, no chains of command, nor predetermined channels of communication.”  Instead, they use cross-disciplinary teams including all functions, communicating directly with each other. Teams self-0rganize and most leaders emerge spontaneously.

As Deloitte’s Cathy Benko and Molly Anderson wrote, “Continuing to invest in the future using yesteryear’s industrial blueprint is futile. The lattice redefines workplace suppositions, providing a framework for organizing and advancing a company’s existing incremental efforts into a comprehensive, strategic response to the changing world of work.”  Add in the circular form’s real-time data hub, and the benefits are even greater, because everyone on these self-organizing teams works from the same data, at the same time.

You can begin to build such a cyclical company with several incremental IoT-based steps.

One of the most promising is making the product design process cyclical. Designers used to work in a vacuum: no one really knew how the products functioned in the field, so it was hard to target upgrades and improvements. Now, GE has found it can radically alter not only the upgrade process, but also the initial design as well:

“G.E. is adopting practices like releasing stripped-down products quickly, monitoring usage and rapidly changing designs depending on how things are used by customers. ‘We’re getting these offerings done in three, six, nine months,’ (Vice-President of Global Software William Ruh said). ‘It used to take three years.’”

New IoT and data-analytics tools are coming on the market that could facilitate such a shift. GE’s new tool, “Digital Twins,” creates a wire-frame replica of a product in the field (or, for that matter, a human body!) back at the company. Coupled with real-time data on its status, it lets everyone who might need to analyze a product’s real-time status (product designers, maintenance staff, and marketers, for example) to do so simultaneously.

The second step toward a cyclical organization is breaking down information silos.

Since almost every department has some role in creation and sales of every product, doesn’t it make sense to bring them together around a common set of data, to explore how that data could trigger coordinated actions by several departments? 

Collaborative big-data analysis tools such as GE’s Predix, SAP’s HANA, and Tableau facilitate the kind of joint scrutiny and “what-if” discussions of real-time data that can make circular teamwork based on IoT-data sharing really achieve its full potential.

The benefits are even greater when you choose to really think in circular terms, sharing instant access to that real-time data not only companywide, but also with external partners, such as your supply chain and distribution network – and even customers – not just giving them some access later on a linear basis.  For example, SAP has created an IoT-enabled vending machine. If a customer opts in, s/he is greeted by name, and may be offered “your regular combination” based on past purchases, and/or a real-time discount. That alone would be neat from a marketing standpoint, but SAP also opened the resulting data to others, resulting in important logistics improvements. Real-time machine-to-machine (M2M) data about sales at the new vending machines automatically reroute resupply trucks to those machines currently experiencing the highest sales. 

With the IoT, sharing data can make your own product or service more valuable. With the Apple HomeKit, you can say “Siri, it’s time for bed,” and the Hue lights dim, Schlage lock closes, and Ecobee thermostat turns down. By sharing real-time IoT data, each of these companies’ devices become more valuable in combinations than they are by themselves.

Hierarchical and linear management is outmoded in the era of real-time data from smart devices. It is time to begin to replace it with a dynamic, circular model with IoT data as its hub.

Liveblogging #IoT @ #Liveworx 2016 — day 2

Colin Angle, CEO, iRobot:

  • smart home: people have hard time learning how to use current generation of smart home devices. Unacceptable delay in activation. we need “just live your life, and the house does the right thing.” Shouldn’t have to pull out phone.  Will be aware of your location, act naturally.
  • “Need metaphor of the room to exist” — and robot will do that. Cool: Future iRobot could do that while doing its own job. New generation of iRobot has mapped 1/2 billion sq. feet in less than a year.
  • Would be a lot cooler if you can just buy a smart bulb, screw it in, and it would just work without having to do anything.
  • Pogue: how do you deal with the criticism that iRobot LOOKS as if it is cleaning randomly? Angle: Customers just cared that it actually did the job. “Just make it clean better” — I don’t care how long it takes, because I’m not there.
  • Next generation of robotics will be manipulation.
  • Angle: “if you’re worried about AI taking over, don’t worry about me, worry about the marketing guys.  … I just vacuum floors.”  This is so funny: “I used to be a self-respecting robot scientist, but it wasn’t until I became a vacuum salesman that I made any money.”

Eric Schaeffer, Accenture:

  • significant change, affecting both demand and supply. No industry unaffected.
  • to remain competitive, countries and companies will have to be at edge of innovation. Faster than ever.
  • strategies focused on cost-cutting less effective than emphasis on new products
  • World Economic Forum looking at impact of internet on business and society
    • 1st report: industrial internet of things & how it would transform industries. Adoption accelerating.
    • 3-4 yrs. from now, major structural changes, massively transformative (but you can begin w/ incremental change).
    • only 7% of 500 companies surveyed said they had comprehensive IoT strategy.
  • illustrations: water distribution network, dramatic time savings in time to install plane seats.
  • where’s the value? integrate smart products and back-office systems for IoT and As-a-Service Enabled approach.
  • Moving to multi-dimensional definition of a product.
  • Companies will become platforms
  • Sales models will move to as-a-service
  • They have identified 30% “uplift” for generic company. Specific improvements from digitization of the enterprise varies from one industry to another
  • Examples:
    • a Euro telecoms company: using a Google Glass-style product for field technicians at job sites and to capture data in field. 20-40% productivity gains.
    • pay-per-use vehicle services: a French tire company that wants to create 1 b Euro biz in “mobility.” — from selling tires to selling outcomes! Money-back guarantee. 2.5 liters reduction in gas use for 100 km driven — huge reduction in trucking companies. 
    • connected homes: working with multiple clients to define what the services will be.
  • Scope and scale of changes acute.
  • Recent survey: 42% of companies have said improvement has been in how they interact with customers.
  • Leading companies moving from product push to creating value by:
    • focusing on higher value solutions
    • focusing on enhanced experience
    • focusing on customer outcomes.
  • still focus on the what, but also the how!
  • dramatic shift to “Total Experience Innovation.”
    • Be Solution Centric: all centered on customer
    • Build an Insight Platform: continuously renew
    • Drive Pivotal Leaders: find right leaders.
  • Examples:
    • ALS patients: helping them regain control of their lives through wearables, displays, etc. done with Phillips.
    • industrial equipment manufacturer: breaking silos. Innovation digital factory: to instill connectivity into the biz, and build outcome-based offers, and increasing level of engagement with customers.
  • Future:
    • implantable technologies
    • wearable internet
    • IoT everywhere
    • connected home
    • driverless cars
    • robotics
    • sharing economy

Here’s the main event!  Prof. Michael Porter, iRobot’s Colin Angle & PTC’s Jim Heppelmann on IoT transformation:

  • Porter & Heppelmann’s research collaboration on IoT: he was a PTC board member. “Magical opportunity”
  • Porter: both products and internal operations are changing due to IoT
  • Porter: still in early stages of industrial conversion
  • Porter: IoT is wrong term: real emphasis is change in products and what they can do. Embedding in service companies. Every service business will be affected.
  • Heppelmann: the IoT also affects how the customer operates the product.
  • Angle: iRobot has jumped into IoT with both feet. Touches every aspect of their biz.
  • Heppelmann: missed the human element in this. That led to their AR initiative, so people could relate to the new products in ways that are both physical and digital.
  • Angle: iRoomba sending data back in real time on how it’s being used. No more focus groups! Robot part of design team.
  • Heppelmann: fundamentally different design process now.
  • Porter: who collects, who decides how to use the data? New chief data officer position.
  • Angle: who is best to handle the data? Idea of chief data officer interesting. Product ID a new competency.
  • Porter: starting to see new organizational structures pop up. Becoming possible to sell almost anything as a service.
  • Heppelmann: “devops” — combine development & operations. Chief Data Officer — whose job is it to decide what the data is telling various departments?
  • Porter: can’t have handoffs between each group, because you need continuing dialogue.
  • Heppelmann: industrial companies can learn from software companies, with techniques such as agile dev in software.  Continuous improvement. Also, “customer analytics.”

 

Day 2, Live Blogging from SAP’s IoT2016 Internet of Things Event

I’m up first this morning, & hope to lift attendees’ vision of what can be achieved with the Internet of Things: sure, cool devices and greater efficiency are great, but there’s so much more: how about total transformation of businesses and the economy, to make them more creative, precise, and even environmentally sustainable?

I’ve just revised my 4 IoT Essential Truths, the heart of my presentation, bumping make privacy and security the highest priority from number 4 to number 1 because of the factors I cited last week. I’ll draw on my background in crisis management to explain to the engineers in attendance, who I’ve found have a problem with accepting fear because it isn’t fact-based, how losing public trust could kill the IoT Golden Goose.

I’ll go on to explain the three other Essential Truths:

  • Share Data (instead of hoarding it, as in the past)
  • Close the Loop (feed that data back so there are no loose ends, and devices become self-regulating
  • Rethink Products so they will contain sensors to feed back data about the products’ real-time status, and/or can now be marketed not as products that are simply sold, but services that both provide additional benefits to customers while also creating new revenue streams for the manufacturer.

I’ll stress that these aren’t just truisms, but really difficult paradigm shifts to accomplish. They’re worth it, however, because making these changes a reality will allow us to leave behind old hierarchical and linear organizational structures that made sense in an age of limited and hard-t0-share data. Instead, we can follow the lead of W.L. Gore and its cyclical “lattice management,” in which — for the first time — everyone can get the real-time data they need to do their jobs better and make better decisions. Equally important, everyone can share this data in real time, breaking down information silos and encouraging collaboration, both within a company and with its supply chain and distribution network — and even with customers.

Amen.


Back with Michael Lynch of SAP!

  • we can change the world and enhance our understanding greater than ever.
  • can help us solve global warming.
  • great case study on heavy truck predictive maintenance in GoldCorp Canadian gold mines.
  • IoT maturity curve:
  • Critical question: who are you in a connected future?  Can lead to re-imaginging your corporate role.
  • UnderArmour is now embedding monitors into clothing.
  • Tennant makes cleaning equipment. Big problem with lost machines, now can find them quickly.
  • Asset Intelligence Network — Facebook for heavy equipment — SAP will launch soon.
  • example of a tractor company that’s moving to a “solutions-based enterprise.” What is the smallest increment of what you do that you could charge customer. Like the turbine companies charging for thrust.

SAP strategy:

  • “Our solution strategy is to grow by IoT-enabling core industry, and providing next generation solutions for millions of human users, while expanding our platform market by adding devices.”
  • they have an amazing next-gen. digital platform. More data flow through there than Alibaba & Amazon!
  • CenterPoint Energy — correlating all sorts of data such as smart meter & weather. Better forecasting.
  • Doing a new home-based diabetes monitoring system with Roche.
  • Doing a lot of predictive maintenance.
  • Connected mining.
  • Building blocks:
    • Connect (SAP IoT Starter Kit)
    • Transform
    • Re-imagine

Ending the day with my presentation on first steps for companies to take in beginning an IoT strategy, with special emphasis on applying analytical tools such as HANA to your current operations, and building “precision operations” by giving everyone who needs it real-time data to improve their job performance and decision-making. Much of the presentation will focus on GE, with its “Brilliant Factories” initiative!

Live Blogging from SAP’s HANA IoT event

Hmm. Never been to Vegas before: seems designed to bring out the New England Puritan in me. I’ll pass on opulence, thank you very much…

 SAP HANA/ IoT Conference

SAP HANA/ IoT Conference

Up front, very interested in a handout from Deloitte, “Beyond Linear,” which really is in line with speech I’ll give here tomorrow on the IoT “Essential Truths,” in which one of my four key points will be that we need to abandon the old, linear flow of data for a continuous cyclical one.  According to Deloitte’s Jag Bandia,

“Among users with a complete, 360-degree view of relevant data for each specific process can help avoid missed opportunities. The ‘all data’ approach means relevant data can and should come from anywhere — any application, any system, any process — not just the traditional channels associated with the process.”

Bravo!

First speaker: SAP Global Customers Operations CTO Ifran Khan:

  • “digital disruption”: catalyst for change & imperative to go digital.
  • digression about running going digital (I put in my 30 minutes this morning!!!), creating a totally new way of exercising (fits beautifully with “Smart Aging“!)
  • new macro tech trends are enabling digitalizations: hyper-connectivity, super computing, cloud computing, smart world, and cybersecurity (horrifying stat about how many USB sticks were left in dry cleaning!)
  • those who don’t go digital will go under…. (like John Chambers’ warning about IoT).
  • new opportunities in wide range of industries
  • need new digital architectures — “driving locality of data, integrated as deep as possible into the engine.
  • HOLY COW! He starts talking about a circular, digitally-centered concept, with a buckyball visual.  Yikes: great minds think alike.
  • sez HANA allows a single platform for all digital enterprise computing.
  • running things in real-time, with no latency — music to my ears!

Jayne Landry, SAP:

  • too few in enterprise have real-time access to analytics — oh yeah!
  • “analytics for everyone”
  • “own the outcome”
  • “be the one to know”
  • SAP Cloud for Analytics — “all analytics capabilities in one product.” real-time, embedded, consumer-grade user experience, cloud-based. Looking forward to seeing this one!
  • “Digital Boardroom” — instant insight. Same info available to board also available to shopfloor — oh yeah — democratizing data!

Very funny bit by Ty Miller on using SAP Cloud for Analytics to analyze Area 51 data. Woo Woo!

Ifran Khan again:

  • how to bring it to the masses? Because it’s expensive and difficult to maintain on the premises, extend and build in cloud! Add new “micro services” to SAP HANA cloud platform: SAP Application Integration, Tax Service, Procurement, Customer Engagement, Predictive, and, ta da, IoT.
  • video of Hamburg Port Authority. Absolutely love that and what they’re doing with construction sites!

Jan Jackman, IBM:

  • customers want speed. Cloud is essential. IBM & HANA are partners in cloud…

This guy is sooo neat: Michael Lynch, IoT Extended Supply Chain for SAP (and former opera student!):

  • “Connecting information, people, and things is greatest resource ever to drive insightful action.”
  • “big deal is the big data processing potential is real & chips are cheaper, so you can build actual business solutions”
  • STILL gmbh (forklifts) great example!
  • phase 1: connect w/ billions of internet-enabled things to gain new insights
  • phase II: transform the way you make decisions and take action
  • phase III: re-imagine your customer’s experience.
  • they do design thinking workshops — would luv one of those!
  • great paradigm shift: Hagleitner commercial bathroom supplies
  • Kaeser compressors: re-imaging customer service
  • working with several German car companies on enabling connected driving
  • once again, the  Hamburg Port Authority!!

SAP’s strategy:

  • offers IoT apps. platforms, and facilitates extensions of IoT solutions
  • work closely with Siemens: he’s talked with them about turbine business.
  • SAP has several solutions for IoT
  • Cloud-based predictive maintenance!
  • “social network for assets”: Asset Intelligence Network
  • They did the Harley York PA plant! — one line, 21-day per bike to 6 hrs.  (displays all around the plant with KPIs)
  • 5 layers of connectivity in manufacturing “shop floor to top floor”  SAP Connected Manufacturing
  • They have a IoT Starter Kit — neat
  • SAP Manufacturing Integration and Intelligence
  • SAP Plant Connectivity
  • SAP Event Stream Processor
  • SAP MobiLink
  • SAP SQL Anywhere/SAP ultralite
  • 3rd Party IoT Device Cloud (had never heard of “device cloud” concept — specialize in various industry verticals).

“Becoming an Insight-Driven Organization”  Speakers: Jag Bandla and Chris Dinkel of Deloitte.

  • Deloitte is using these techniques internally to make Deloitte “insight-driven”
  • “an insight-driven organization (IDO) is one which embeds analysis, data, and reasoning into every step of the decision-making process.” music to my ears!
  • emphasis on actionable insight
  • “when humans rely on their own experiences and knowledge, augmented by a stream of analytics-driven insights, the impact on value can be exponential”
  • benefits to becoming an IDO:
    • faster decisions
    • increased revenue
    • decreased cost of decision making
  • challenges:
    • lack of proper tech to capture
    • oooh: leaders who don’t understand the data…
  • 5 enabling capabilities:
    • strategy
    • people
    • process
    • data
    • tech
  • developing vision for analytics
  • Key questions: (only get a few..)
    • what are key purchase drivers for our customers?
    • how should we promote customer loyalty?
    • what customer sentiments are being expressed on social media?
    • how much should we invest in innovation?
  • Value drivers:
    • strategic alignment
    • revenue growth
    • cost reduction
    • margin improvement
    • tech
    • regulation/compliance
  • Organize for success (hmm: I don’t agree with any of these: want to decentralize while everyone is linked on a real-time basis):
    • centralized (don’t like this one, with all analyzed in one central group.. decentralize and empower!)
    • consulting: analysts are centralized, but act as internal consultants
    • center of excellence: central entity coordinates community of analysts across company
    • functional: analysts in functions such as marketing & supply chain
    • dispersed: analysts scattered across organization, little coordination
  • Hire right people! “Professionals who can deliver data-backed insights that create business value — and not just crunch numbers — are the lifeblood of an Insight-Driven Organization”
    • strong quantitative skills
    • strong biz & content skills (understand content and context)
    • strong data modeling & management skills
    • strong IT skills
    • strong creative design skills (yea: techies often overlook the cool design guys & gals)
  • Change the mindset (critical, IMHO!):
    • Communicate: build compelling picture of future to steer people in right direction.
    • Advocate: develop cohort of leaders to advocate for program.
    • Active Engagement: engage key figures to create pull for the program
    • Mobilize: mobilize right team across the organization.
  • How do you actually do it? 
    • improve insight-to-impact with “Exponential Biz Processes” — must rebuild existing business processes!  Involves digital user experience, biz process management, enterprise science, all data, and IT modernization.
      • re-engineer processes from ground up
      • develop intuitive, smart processes
      • enable exception-based management
  • Data:
    • “dark data:” digital exhaust, etc. might be hidden somewhere, but still actionable.
      • they use it for IoT: predictive personalization (not sure I get that straight…).
    • want to have well-defined data governance organization: standards, data quality, etc.
  • Technology: digital core (workforce engagement, big data & IoT, supplier collaboration, customer experience
    • HANA
  • Switch to digital delivery: visualizations are key!
    • allow for faster observations of trends & patterns
    • improve understanding & retention of info
    • empower embedded feeds and user engagement

 

IoT and the Data-Driven Enterprise: Bob Mahoney, Red Hat & Sid Sipes, Sr. Director of Edge Computing, SAP

  • What’s driving enterprise IoT?
    • more connected devices
    • non-traditional interactions such as M2M and H2M
    • ubiquitous internet connectivity
    • affordable bandwidth
    • cloud computing
    • standards-based and open-source software
  • Biz benefits:
    • economic gains
    • new revenue streams (such as sale of jet turbine data)
    • regulatory compliance
    • efficiencies and productivity
    • ecological impact
    • customer satisfaction
  • example of Positive Train Control systems to avert collisions. Now, that can be replaced by “smarter train tech”
  • SAP and edge computing (can’t move all of HANA to edge, but..)
    • improve security in transmission
    • reduce bandwidth need
    • what if connection goes down
    • actual analysis at the edge
    • allows much quicker response than sending it to corporate, analyzing & send it back
    • keep it simple
    • focused on, but not limited to, IoT
  • they can run SQL anywhere on IoT, including edge: SQL Anywhere
  • Red Hat & SAP doing interesting combination for retail, with iBeacons, video heat map & location tracking: yields real insights into consumer behavior.

Claro’s IoT Strategy Creation Guide: important in own right & symbolically

IoT_strategy_cards

Claro IoT Service Diagram Cards — collect the whole set!

Some IoT advances are as important symbolically (especially as key steps in the IoT’s maturation) as in their own right.

I consider Claro Partners‘s new “A Guide to Succeeding in the Internet of Things” in that vein, both showing that it’s not just enough to create a whizbang IoT device or app — you need a methodical strategy to maximize the benefits– and providing a very practical tool to create such a strategy. Written as the IoT reaches the top of the Gartner Hype Cycle, it aims at helping readers identify and meet real user needs and create viable business models. Based on several conversations at last night’s Boston IoT Meetup, it couldn’t be more timely, as (for example) smart home device sales slump, as reflected in Quirky’s bankruptcy.

Claro, in case you haven’t heard about them before, is headquartered in my favorite “smart city,” Barcelona, and is known for its Clayton Christensen-style emphasis on the opportunities presented by disruptive change (hmm: wonder if they have wei ji ideograms on the wall, LOL?), particularly with the IoT.

The Guide is a quick read, but can inspire you for a long time to come.

It’s divided into four portions, which I’m guessing codify the process that Claro uses internally to brainstorm strategies for its own clients:

  1. Define the challenge. “Identify a user-centric challenge to solve.”
  2. Ideate* the solution. “Create a solution that provides new value to the user.”
  3. Develop the offer. “Map out the ecosystem and interactions of your product and service.”
  4. Plan for production. “Identify resources needed and conduct gap analysis.”

They suggest you follow these steps sequentially, even if you already have a solution in mind, because “the exercises will help you to refine, develop or rethink it.”

Now for the details, which include very specific steps and some very helpful graphic aids.

First, Define the challenge. They stress you need to avoid being seduced by the lure of doing something just because it’s technologically possible. Make sure it meets a real
human need. The initial categories they suggest include:

    • Human Needs FrameworkAgeing population (sweeeeet! My “smart aging” paradigm shift!)
    • Work-life balance
    • Urban life
    • Health and wellbeing
    • Local Communities
    • Education
    • Sustainability/Shopping
    • Tourism, Family.

Then Claro suggests that your team go through a 30-minute process where it uses the four questions in this “human needs framework,” such as “what do people want to control?” and decide which challenge you’re going to design for (assume you could think big and try for one that meets multiple questions).

Second, Ideate the solution.  Similar to my “What can you do now that you couldn’t do before” question, this one asks you to not just use the IoT to refine a current approach to the issue you identified, but to “reimagine entirely new capabilities and value that an IoT service can deliver.”

This 40-min. process includes defining the person facing the challenge and aspects of their life, then brainstorming solutions to meet their real needs and how the IoT could be used to enable that solution.

Third, Develop the offer. They share my concern about proprietary IoT solutions, (which they label “intranet of things, LOL), and instead remind your team to, IFTTT-like,

IoT Service Diagram

IoT Service Diagram

“take advantage of the ecosystem enabled by the IoT to create interconnected services, experiences and business models.” In this process, which they estimate takes 40 minutes, you print out the IoT Service Diagram Cards (see above — I imagine “flipping” them and trading with the other kids on the playground, until our Moms throw out our collections…) and use them to map out how your idea will work, including drawing the data flow (don’t forget my dictum that data flow must be cyclical with the IoT!).  The important questions to ask — make sure to ask all of them! — include:

  • Will the device just provide information to the user or will it act on that information?
  • What are the specific inputs/outputs of the service? (eg. sight, sounds, touch, taste, smell, temperature)
  • Could the device learn through its use over time and adapt its behaviour accordingly?
  • Could the service use existing devices, data streams or interfaces?

Finally, in the fourth step, (30 minutes? Dream on!) the rubber hits the road, and you

IoT Canvas

IoT Canvas

Plan for Production!  Claro warns, “Don’t underestimate the complexity of bringing to life an offer that spans both the physical and digital, Do map out all the elements you’ll need to successfully develop and deliver your IoT offer.”

On the IoT Canvas, you bring together all the crucial considerations, such as manufacturing and logistics, revenues and costs, that must be nailed down to make the product affordable and profitable.  Specifically, Claro says you need to specifically state the offer’s value proposition to the end user, use the questions in each box on the form as prompts, fill out the rest of the canvas with details of the product and service idea, and write down “which resources, capabilities and processes you have, and which you’d need to acquire (gap analysis).”

I agree with Claro that these four steps, especially the last one, are iterative, and you need to revisit each of them throughout the entire conceptual and production process.

I have no doubt that, as IoT technology (especially miniscule, low-energy sensors) and experience continues to evolve, this process will be refined, but Claro has done the entire IoT industry, especially makers and entrepreneurs, a real service by codifying this approach and being willing to share it — after all, the IoT’s all about collaboration! 


*we’ll let them off with a warning from the Grammar Police this time. However, please, no more management babble in the future, OK?

 

Deloitte provides process for nuanced IoT strategy decisions

So much of the Internet of Things is still in the gee-whiz stage that we haven’t seen much in terms of nuanced IoT strategies. By that I mean ones that carefully weigh tradeoffs between companies and consumers to try to find strategies that are mutually beneficial and recognize there are new factors at play in IoT strategies, such as privacy and data mining, that may have positive or negative consequences for the customer/company interplay.

Deloitte’s “University” has made an important step in that direction with its “Power Struggle: Customers, companies and the Internet of Things” paper, co-authored by Brenna Sniderman and Michael E. Raynor.

In it, they explore how to create sustainable strategies that will be mutually beneficial to the customer and company — which are not always immediately apparent, especially when you explore the subtleties of how these strategies might play out in the new reality of the Internet of Things.

The study’s goal was to understand the factors that can distort IoT’s benefits, and instead create win-win IoT strategies.

Sniderman and Raynor suggest there are four quadrants into which a given strategy might fall:

  1. (the sweet spot!) “All’s well: Sufficient value is created, and that value is shared between customers and companies sufficiently equitably such that both parties are better off and feel fairly treated.
  2. “Hobson’s choice: A Hobson’s choice exists when you’re free to decide but only one option exists; thus, it is really no choice at all…. Even when customers come out ahead compared with their former options, their implied powerlessness can lead to feelings of unfairness.
  3. “Gridlock: In their quest for value capture, both sides are pulled in opposite directions, with neither able to move toward an optimal outcome. Here, both parties recognize IoT enablement as something that should lead to success, but neither party is able to reach it, since their competing interests or different value drivers are working at cross purposes.
  4. “Customer is king: Although particular IoT deployments might make economic sense for companies, customers end up capturing a disproportionate share of the new value created, pulling this outcome more in the customers’ favor; Craigslist is an obvious example.”

According to the authors, a key to finding the win-win, “all’s well” solution is the Information Value Loop (which I first discussed last Spring) that creates value out of the vast increase in information made possible by the IoT.

As I mentioned then, “This fits nicely with one of my IoT ‘Essential Truths,’ that we need to turn linear information flows into cyclical ones to fully capitalize on the IoT.” When you do that, it’s possible to design continuous improvement processes that feed back data from actual users to fine tune products and processes.  GE has found it leads to much shorter iterative loops to design improved versions of its products.

Here’s the gussied-up version of the cool hand-drawn visualization from the Deloitte brainstorming session that led to the Information Value Loop (print it & place it on your wall next to the one on privacy and security that I wrote about a while ago):

Deloitte Information Value Loop

The information no longer flows in linear fashion: it’s created from using sensors to record how things act in the real world, then goes through the various stages of the loop, each of which is made possible by one of the new technologies enabling the IoT.  The goal is either enhanced M2M integration among things, or improved actions by humans, and, to be sustainable over time:

“A value loop is sustainable when both parties capture sufficient value, in ways that respect important non-financial sensibilities. For example, retailer-specific and independent shopping apps can use past browsing and purchasing history—along with other behaviors—to suggest targeted products to particular customers, rather than showing everyone the same generic products, as on a store shelf. Customers get what they want, and companies sell more.

…  “The amount of value created by information passing through the loop is a function of the value drivers identified in the middle. Falling into three generic categories—magnitude, risk, and time—the specific drivers listed are not exhaustive but only illustrative. Different applications will benefit from an emphasis on different drivers.”

OK, so how does this theory play out?

Sniderman and Raynor picked a range of IoT-informed strategies to illustrate the concept, some of which may include unintended consequences that would harm/turn off customers or companies. For example, “An ill-considered push for competitive advantage could well overreach and drive away skittish customers. Alternatively, building too dominant an advantage may leave customers feeling exploited or coerced, a position unlikely to prove viable in the long term.”

Understanding the underlying structure of each type of loop is critical, because they naturally pull an IoT strategy in a particular, divergent way.

The example they pick to illustrate the “all’s well” quadrant of results is the dramatic increase in built-in diagnostic technology in cars.  This is of great personal interest: genetic testing has revealed that I am one of the approximately 10% of men who are missing the male car gene: I can’t stand the things, and view them as a big block of metal and plastic just waiting to develop problems (or, ahem, get hit by deer …), so I need all the help I can get. Sniderman and Raynor zero in on maintenance as one area for win-win benefits for drivers and dealers through the IoT:

“Customers often have little understanding of which repairs are necessary, feel inconvenienced by having to go without their car during maintenance periods, and are frustrated by potential overcharges. In response, automakers are embedding sensors that can run a wide range of reliable diagnostics, allowing a car to “self-identify” service issues, rather than relying on customers (“Where’s that squeaking coming from?”) or mechanics (“You might want to replace those brake pads, since I’ve already got the wheels off”). This creates a level of objectivity of obvious customer value and enables automakers to differentiate their products. Interactive features that work with customers’ information can further add value by, for example, potentially syncing with an owner’s calendar to schedule a dealership appointment at a convenient time and reserving a loaner vehicle for the customer, pre-programmed with his preferences to minimize the frustration of driving an unfamiliar car.

In this scenario, both parties collaborate to provide and act on data, in a mutual exchange of value. The customer captures value in multiple ways: He enjoys increased convenience and decreased frustration, improved vehicle performance and longer operating life, reduced maintenance charges, and—since almost everything about this interaction is automated—fewer occasions for perceived exploitation at the hands of unscrupulous service providers.

Value capture extends to companies in the form of ongoing customer interaction. Linking maintenance programming to the dealership encourages customers to return for tune-ups rather than go elsewhere, ideally leading to continued purchases in the long term. OEMs can also access data regarding vehicle maintenance issues and may be able to identify systematic malfunctions worthy of greater attention. Dealers also have an opportunity to make inroads into an untapped market: Currently, just 30 percent of drivers use the dealer for routine maintenance…”

Kumbaya! But then there’s the opposite extreme, according to Sniderman and Raynor, represented by smart home devices, which would lead to the lose-lose, gridlock scenario.  I think they seriously underestimate the understanding already by manufacturers in the field that they need to embrace open standards in order to avoid a range of competing standards (Zigbee, Bluetooth, etc.) that will force consumers to invest in a variety of proprietary, incompatible hubs, and therefore discourage them from buying anything at all.  All you have to do is look at new hubs, such as Amazon’s Echo, which can control devices from WeMo, Hue, Quirky, Wink — you name ’em, to realize that sharing data is already the norm with smart home devices.

Because this missive is getting long, I’ll leave it to you, dear reader, to investigate Sniderman & Raynor’s examples of the “customer is king” scenario, in which the customer grabs too much of the benefit (have to admit, a lot of the location-based IoT retail incentives still give me the creeps: I hate shopping under the best of circumstances, and having something pop up on my phone offering me an incentive based on my past purchases makes a bad experience even worse. How about you?); and the “Hobson’s choice” one, in which usage-based car insurance runs amok and insurers begin to charge unsafe drivers a surcharge — as documented by the devices such as Progressive’s “Snapshot” (I was dismayed to read in the article that Progressive is in fact doing that in Missouri, although I guess it’s a logical consequence of having objective evidence that someone consistently drives unsafely).

I can’t help thinking that the 800-pound gorilla in the room in many of these situations are the Scylla and Charybdis of the IoT, threats to privacy and security, and that makes it even more important that your IoT strategies are well thought out.

They conclude that, from my perspective, data isn’t just enough, you also need the decidedly non-technical tools of judgment and wisdom (aided by tools such as their Information Value Loop) to come up with a sustainable, mutually advantageous IoT strategy:

“Identifying where the bottlenecks lie (using the Information Value Loop), how each party is motivated to respond, and seeking to shape both incentives and the value loop itself puts companies more in control of their destinies.

“Second, taking a hard look at who benefits most from each IoT-enabled transaction, understanding when a lopsided value-capture outcome tips too far and becomes unsustainable, and taking steps to correct it may also lead to long-term success.

“Lastly, an honest assessment of where IoT investments may not have an appreciable benefit—or may decrease one’s potential for value capture—is just as crucial to a company’s IoT strategy as knowing the right places to invest.”

I may quibble with some of their findings, such as those about smart homes, but bravo to Sniderman and Raynor for beginning what I hope is a spirited and sustained dialogue about how to create sustainable, mutually-advantageous IoT strategies!  I’ve weighed in with my Essential Truths, but what are you thinking about this critical issue, often overlooked in our concentration on IoT technologies? 

McKinsey IoT Report Nails It: Interoperability is Key!

I’ll be posting on various aspects of McKinsey’s new “The Internet of Things: Mapping the Value Beyond the Hype” report for quite some time.

First of all, it’s big: 148 pages in the online edition, making it the longest IoT analysis I’ve seen! Second, it’s exhaustive and insightful. Third, as with several other IoT landmarks, such as Google’s purchase of Nest and GE’s divestiture of its non-industrial internet division, the fact that a leading consulting firm would put such an emphasis on the IoT has tremendous symbolic importance.

McKinsey report — The IoT: Mapping the Value Beyond the Hype

My favorite finding:

“Interoperability is critical to maximizing the value of the Internet of Things. On average, 40 percent of the total value that can be unlocked requires different IoT systems to work together. Without these benefits, the maximum value of the applications we size would be only about $7 trillion per year in 2025, rather than $11.1 trillion.” (my emphasis)

This goes along with my most basic IoT Essential Truth, “share data.”  I’ve been preaching this mantra since my 2011 book, Data Dynamite (which, if I may toot my own horn, I believe remains the only book to focus on the sweeping benefits of a paradigm shift from hoarding data to sharing it).

I was excited to see that the specific example they zeroed in on was offshore oil rigs, which I focused on in my op-ed on “real-time regulations,” because sharing the data from the rig’s sensors could both boost operating efficiency and reduce the chance of catastrophic failure. The paper points out that there can be 30,000 sensors on an rig, but most of them function in isolation, to monitor a single machine or system:

“Interoperability would significantly improve performance by combining sensor data from different machines and systems to provide decision makers with an integrated view of performance across an entire factory or oil rig. Our research shows that more than half of the potential issues that can be identified by predictive analysis in such environments require data from multiple IoT systems. Oil and gas experts interviewed for this research estimate that interoperability could improve the effectiveness of equipment maintenance in their industry by 100 to 200 percent.”

Yet, the researchers found that only about 1% of the rig data was being used, because it rarely was shared off the rig with other in the company and its ecosystem!

The section on interoperability goes on to talk about the benefits — and challenges — of linking sensor systems in examples such as urban traffic regulation, that could link not only data from stationary sensors and cameras, but also thousands of real-time feeds from individual cars and trucks, parking meters — and even non-traffic data that could have a huge impact on performance, such as weather forecasts.  

While more work needs to be done on the technical side to increase the ease of interoperability, either through the growing number of interface standards or middleware, it seems to me that a shift in management mindset is as critical as sensor and analysis technology to take advantage of this huge increase in data:

“A critical challenge is to use the flood of big data generated by IoT devices for prediction and optimization. Where IoT data are being used, they are often used only for anomaly detection or real-time control, rather than for optimization or prediction, which we know from our study of big data is where much additional value can be derived. For example, in manufacturing, an increasing number of machines are ‘wired,’ but this instrumentation is used primarily to control the tools or to send alarms when it detects something out of tolerance. The data from these tools are often not analyzed (or even collected in a place where they could be analyzed), even though the data could be used to optimize processes and head off disruptions.”

I urge you to download the whole report. I’ll blog more about it in coming weeks.