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!

 

 

Gartner study confirms senior managers don’t understand IoT

Posted on 21st February 2015 in Internet of Things, M2M, management, manufacturing, marketing, strategy

The “Managing the Internet of Things Revolution” e-guide I wrote for SAP was aimed at C-level executives. Even though it’s proven popular enough that the company is translating it into several languages, it appears we need to redouble our efforts to Managing_the_Internet_of_Things_Revolutionbuild IoT awareness among executives.

I say that because Gartner has just come out with a survey confirming my suspicions: even though a lot of companies now think the IoT will have a major effect on them, they’re clueless about how to manage it and most have yet to launch major IoT initiatives.

In fact, “many survey respondents felt that the senior levels of their organizations don’t yet have a good understanding of the potential impact of the IoT.” (my emphasis)

 

That’s despite the fact that a key conclusion of my guide was that (even though the IoT is a long way from full maturity) companies can and should begin their IoT strategies and implementation now, because they can already achieve significant savings in operating costs, improve marketing, and create new revenue streams with the current early stage sensors and analytical tools. Getting started will also build their confidence and familiarity with IoT tools and strategy before they begin more dramatic transformational strategies.

Consider these findings from the survey of 463 business and IT leaders:

  • 40% of companies think the IoT will at least bring new short-term revenue and cost reduction opportunities in the next three years — or perhaps even transform them. More than 60% think that will be true over 5 years or more.
  • Fewer than 25% said their company had “established clear business leadership for the IoT,” — even among the companies predicting a significant  – this includes those who said they expect the IoT to have a significant or transformational impact, says Gartner (however, 35% of them came from this group).
  • Yet, few have delegated specific responsibility for IoT strategy and management: “… less than one-quarter of survey respondents has established clear business leadership for the IoT, either in the form of a single organizational unit owning the issue or multiple business units taking ownership of separate IoT efforts.”
  • “attitudes toward the IoT vary widely by industry. For example, board of directors’ understanding of the IoT was rated as particularly weak in government, education, banking and insurance, whereas the communications and services industries scored above-average ratings for senior executive understanding of the IoT.”

Gartner concluded most companies have yet to really create IoT strategies:

“‘The survey confirmed that the IoT is very immature, and many organizations have only just started experimenting with it,’ said Nick Jones, vice president and distinguished analyst at Gartner. ‘Only a small minority have deployed solutions in a production environment. However, the falling costs of networking and processing mean that there are few economic inhibitors to adding sensing and communications to products costing as little as a few tens of dollars. The real challenge of the IoT is less in making products ‘smart’ and more in understanding the business opportunities enabled by smart products and new ecosystems.’ However, a lack of clear business or technical leadership is holding back investment in the technology.” (my emphasis)

In line with my current preoccupation, privacy and security, the survey did show companies are concerned with both issues, as well as with finding talented new staff who understand the IoT and how to benefit from it. According to Steve Kleyhans, Gartner’s research vp:

 “While a single leader for the IoT is not essential, leadership and vision are important, even in the form of several leaders from different business units. We expect that over the next three years, more organizations will establish clear leadership, and more will recognize the value of some form of an IoT center of excellence because of the need to master a wide range of new technologies and skills.”

If you haven’t launched any IoT projects or begun to create a strategy, the writing’s on the wall: get going!


Carpe diem: I take this survey as an omen that there’s a desperate need for When Things Can Talk: profiting from the Internet of Things revolution,” my proposed full-length book on IoT corporate strategy. Let me know if you can suggest a possible publisher!

Management Challenge: Lifeguards in the IoT Data Lake

In their Harvard Business Review November cover story, How Smart, Connected Products Are Transforming Competition, PTC CEO Jim Heppelmann and Professor Michael Porter make a critical strategic point about the Internet of Things that’s obscured by just focusing on IoT technology: “…What makes smart, connected products fundamentally different is not the internet, but the changing nature of the “things.”

In the past, “things” were largely inscrutable. We couldn’t peer inside massive assembly line machinery or inside cars once they left the factory, forcing companies to base much of both strategy and daily operations on inferences about these things and their behavior from limited data (data which was also often gathered only after the fact).

Now that lack of information is being removed. The Internet of Things creates two unprecedented opportunities regarding data about things:

  • data will be available instantly, as it is generated by the things
  • it can also be shared instantly by everyone who needs it.

This real-time knowledge of things presents both real opportunities and significant management challenges.

Each opportunity carries with it the challenge of crafting new policies on how to manage access to the vast new amounts of data and the forms in which it can be accessed.

For example: with the Internet of Things we will be able to bring about optimal manufacturing efficiency as well as unprecedented integration of supply chains and distribution networks. Why? Because we will now be able to “see” inside assembly line machinery, and the various parts of the assembly line will be able to automatically regulate each other without human intervention (M2M) to optimize each other’s efficiency, and/or workers will be able to fine-tune their operation based on this data.

Equally important, because of the second new opportunity, the exact same assembly line data can also be shared in real time with supply chain and distribution network partners. Each of them can use the data to trigger their own processes to optimize their efficiency and integration with the factory and its production schedule.

But that possibility also creates a challenge for management.

When data was hard to get, limited in scope, and largely gathered historically rather than in the moment, what data was available flowed in a linear, top-down fashion. Senior management had first access, then they passed on to individual departments only what they decided was relevant. Departments had no chance to simultaneously examine the raw data and have round-table discussions of its significance and improve decision-making. Everything was sequential. Relevant real-time data that they could use to do their jobs better almost never reached workers on the factory floor.

That all potentially changes with the IoT – but will it, or will the old tight control of data remain?

Managers must learn to ask a new question that’s so contrary to old top-down control of information: who else can use this data?

To answer that question they will have to consider the concept of a “data lake” created by the IoT.

“In broad terms, data lakes are marketed as enterprise wide data management platforms for analyzing disparate sources of data in its native format,” Nick Heudecker, research director at Gartner, says. “The idea is simple: instead of placing data in a purpose-built data store, you move it into a data lake in its original format. This eliminates the upfront costs of data ingestion, like transformation. Once data is placed into the lake, it’s available for analysis by everyone in the organization.”

Essentially, data that has been collected and stored in a data lake repository remains in the state it was gathered and is available to anyone, versus being structured, tagged with metadata, and having limited access.

That is a critical distinction and can make the data far more valuable, because the volume and variety will allow more cross-fertilization and serendipitous discovery.

At the same time, it’s also possible to “drown” in so much data, so C-level management must create new, deft policies – to serve as lifeguards, as it were. They must govern data lake access if we are to, on one hand, avoid drowning due to the sheer volume of data, and, on the other, to capitalize on its full value:

  • Senior management must resist the temptation to analyze the data first and then pass on only what they deem of value. They too will have a crack at the analysis, but the value of real-time data is getting it when it can still be acted on in the moment, rather than just in historical analyses (BTW, that’s not to say historical perspective won’t have value going forward: it will still provide valuable perspective).
  • There will need to be limits to data access, but they must be commonsense ones. For example, production line workers won’t need access to marketing data, just real-time data from the factory floor.
  • Perhaps most important, access shouldn’t be limited based on pre-conceptions of what might be relevant to a given function or department. For example, a prototype vending machine uses Near Field Communication to learn customers’ preferences over time, then offers them special deals based on those choices. However, by thinking inclusively about data from the machine, rather than just limiting access to the marketing department, the company shared the real-time information with its distribution network, so trucks were automatically rerouted to resupply machines that were running low due to factors such as summer heat.
  • Similarly, they will have to relax arbitrary boundaries between departments to encourage mutually-beneficial collaboration. When multiple departments not only share but also get to discuss the same data set, undoubtedly synergies will emerge among them (such as the vending machine ones) that no one department could have discovered on its own.
  • They will need to challenge their analytics software suppliers to create new software and dashboards specifically designed to make such a wide range of data easily digested and actionable.

Make no mistake about it: the simple creation of vast data lakes won’t automatically cure companies’ varied problems. But C-level managers who realize that if they are willing to give up control over data flow, real-time sharing of real-time data can create possibilities that were impossible to visualize in the past, will make data lakes safe, navigable – and profitable.